{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Stability map with MEGNO and WHFast\n",
    "In this tutorial, we'll create a stability map of a two planet system using the chaos indicator MEGNO (Mean Exponential Growth of Nearby Orbits) and the symplectic integrator WHFast (Rein and Tamayo 2015).\n",
    "\n",
    "We will integrate a two planet system with massive planets. We vary two orbital parameters, the semi-major axis $a$ and the eccentricity $e$. Let us first define a function that runs one simulation for a given set of initial conditions $(a, e)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-24T21:08:23.195270Z",
     "start_time": "2023-09-24T21:08:23.181079Z"
    }
   },
   "outputs": [],
   "source": [
    "def simulation(par):\n",
    "    a, e = par # unpack parameters\n",
    "    sim = rebound.Simulation()\n",
    "    sim.integrator = \"whfast\"\n",
    "    sim.ri_whfast.safe_mode = 0\n",
    "    sim.dt = 5.\n",
    "    sim.add(m=1.) # Star\n",
    "    sim.add(m=0.000954, a=5.204, M=0.600, omega=0.257, e=0.048)\n",
    "    sim.add(m=0.000285, a=a, M=0.871, omega=1.616, e=e)\n",
    "    sim.move_to_com()\n",
    "    \n",
    "    sim.init_megno()\n",
    "    sim.exit_max_distance = 20.\n",
    "    try:\n",
    "        sim.integrate(5e2*2.*np.pi, exact_finish_time=0) # integrate for 500 years, integrating to the nearest\n",
    "        #timestep for each output to keep the timestep constant and preserve WHFast's symplectic nature\n",
    "        megno = sim.megno() \n",
    "        return megno\n",
    "    except rebound.Escape:\n",
    "        return 10. # At least one particle got ejected, returning large MEGNO."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try this out and run one simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-24T21:08:24.035399Z",
     "start_time": "2023-09-24T21:08:23.946126Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0535548978104345"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import rebound\n",
    "import numpy as np\n",
    "simulation((7,0.1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The return value is the MEGNO. It is about 2, thus the system is regular for these initial conditions. Let's run a whole array of simulations. We will use the multiprocess module to run the simulations in parallel. If the following line throws you an ImportError, install the module with `pip install multiprocess`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-24T21:08:24.770700Z",
     "start_time": "2023-09-24T21:08:24.757093Z"
    }
   },
   "outputs": [],
   "source": [
    "from multiprocess import Pool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-24T21:08:25.796868Z",
     "start_time": "2023-09-24T21:08:25.182288Z"
    }
   },
   "outputs": [],
   "source": [
    "with Pool() as pool:\n",
    "    Ngrid = 80\n",
    "    par_a = np.linspace(7.,10.,Ngrid)\n",
    "    par_e = np.linspace(0.,0.5,Ngrid)\n",
    "    parameters = []\n",
    "    for e in par_e:\n",
    "        for a in par_a:\n",
    "            parameters.append((a,e))\n",
    "    results = pool.map(simulation,parameters)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On my laptop, this takes only half a second.\n",
    "\n",
    "Let's plot it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-24T21:08:26.697801Z",
     "start_time": "2023-09-24T21:08:26.263972Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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+q9ni2AtHLt74Q36h2Y9hLdb+6vN6JeetODs7IzIyEgDQunVr7NixAx9//DHmzp2ru01OTg6WLl2KiRMn3nL/devWhb+/P44ePcqJGhEREd2erLYyQTn3YTQakZeXV+qY5cuXIy8vD089Jf9yWtKZM2dw8eJFBAfLq3hUBk7UiIiIyO6NHTsWPXr0QO3atZGVlYXFixcjPj4e69atAwAMGDAAoaGhSn7bvHnz0Lt3b6VAIDs7GxMmTMATTzyBoKAgHDt2DKNHj0ZkZCRiYmJs9rxuhRM1IiIisoilzWpL24+5UlJSMGDAAJw/fx7e3t5o3rw51q1bhwcffBAAkJiYCAcH06+wDx8+jE2bNuF///ufsj9HR0fs27cPCxcuRHp6OkJCQtCtWzdMmjTJrnqpcaJGREREFrF2jpo55s2bV+rfx8fHK7EGDRpA0+T8czc3t+K7cfaME7VrCnIKYChiMQFVroKC8m2f8IRcCNBv9X1KTPvzqDg2OudNJVYzR05WXhJgnwUklV040DPvXTH+o4t6bi0Za4ntSerF9G259li1nd1r/qoN/c8NV2LPTl9a7mMwLluoxLLz7adNBFUOTtSIiIjIIgaDAwwO5W/FajDwBsmtcKJGREREFrHaV58WrPV5p+LKBERERER2infUiIiIyCKVUfV5p+JE7Ro3Pzc4uDlV9mEQlcuBQ3K83kMPK7HdKTvFsWfc1eR2qRjBEm3vkT9qdmytmI7qXR73UWK/fpteIY8lsaQQoLxFA3q+HaNzMZip37f3ivGlj/9Rrv3aq70b1RUEDuiMHXt8jxIrzJWv5c0b1PdOhwd+F8caWkQqsbPz1LYSAFDNxbH4vzVosHXJASdqtsOvPomIiIjsFO+oERERkUUMjrBSMYEVDqaK40SNiIiILGIva33eCfjVJxEREZGd4h21ay5fuAyDK08H3d6Sdz8gxvv9uFKJ1XSXi2ceFGKRqWni2MlmHtfxvyumaECPLQsHqqqqUDTQ/8r7YnyJ2yglpleII/n4+7+VmE9tH/N3oOOZxONKLD/HjOVKKmH1AhYT2A5nJkRERGQRNry1HX71SURERGSneEeNiIiILGIwWOmrTwPvqN0KJ2rXODo7wuDseOuBVGVF960hxn9ZdtHsffTb9IgSW9rx+zIfU2l6jayjxKpH3C+OHeF3Ton5fLlOHDuxh4cSO7FL3d4SF+UUtyqhf/7HSmyJ8/BKOJI7Q/crE8T4WrfxSkzKRbPEq7MaivH8gylKzFgo95mQ5jL9094Wx7618lsl5lPbWz6G7Pzi/9byCnFFHFWBrPTVJ6yxjyqOX30SERER2SneUSMiIiKLGBwcYHAo/70ea+yjquNEjYiIiCzC9hy2w6ksERERkZ3iHbVrnD2c4eAmNwClO4MlRQN6KqpwQOLWr7USq7dihTj2UJb6W2vmuSxxbPxH7dXgx7stO7ib9F1yjxhf1n9rufZrD8pbOPDPL9uK8W8G7CjXfi3RZ87dSmz5i3ts9vhPvugrxhfNuaTEpKIBS332jfreeeGfu5TYow1ritufCFILbhKSssWxPx9Tn8M9nSeJY498E6XEnPeeF8cai7Qbf8i3bUNpAHBwNMDBCoUA1thHVWeXd9RmzZqF8PBwuLq6on379ti+fbtZ2y1duhQGgwG9e/eu2AMkIiK6g13/6tMaP1Q6u5uoLVu2DCNHjsT48eOxe/dutGjRAjExMUhJUcuhSzp58iRee+013HfffTY6UiIiIqKKZXcTtY8++giDBw/GoEGD0LhxY8yZMwfVq1fH/PnzdbcpKirCk08+iQkTJqBu3bo2PFoiIqI7z/UlpKzxQ6Wzq4lafn4+du3ahejo6OKYg4MDoqOjsWXLFt3tJk6ciICAADz33HO3fIy8vDxkZmaa/BAREZH5+NWn7dhVMcGFCxdQVFSEwMBAk3hgYCD++usvcZtNmzZh3rx52Lt3r1mPERsbiwkT1M7WgZ4ucGQxAdmpJ2Y0U2LpzVoosV/uCha3d07PV4NT5MKDf/6crMTGtpT3C6iJ0pJa6Rli/AOztr79/P6rnIJxX5ffldi53h119mK7YoKszWdt9lgSqWigIh08a94v6Et+PynG175wrxLrtWSnOLamn5sSa3NpsDh2me/nSqzuvKbi2KM7Kvc1I9uxqztqlsrKysLTTz+Nzz//HP7+/mZtM3bsWGRkZBT/nD59uoKPkoiIqIpxMFxd/qm8P7yjdkt2dUfN398fjo6OSE42/Y0+OTkZQUFByvhjx47h5MmTeOSRG+srGo1X11urVq0aDh8+jHr16pls4+LiAhcXlwo4eiIiojsDG97ajl3dUXN2dkbr1q0RFxdXHDMajYiLi0NUlNpfpmHDhkhISMDevXuLfx599FE88MAD2Lt3L2rVqmXLwyciIiKyKru6owYAI0eOxMCBA9GmTRu0a9cOM2bMQE5ODgYNGgQAGDBgAEJDQxEbGwtXV1c0bWr6/b2Pjw8AKHEiIiKyEkeHqz/W2A+Vyu4man379kVqairGjRuHpKQktGzZEmvXri0uMEhMTIRDBSzievp8Fgyudnc6yIaq/f2gGC+8a72Nj0S1ckSCEpsXqn6Fvz5QTREAgENNApRYjXp+4tgNj9dTYhNz5K7rwEGduKm9Ax4X478Medes7W83s3Ry1ZcKsa1J+yvkGNzUHHZcuSKPdW8mdeAvvXfl7Sz56X8osSWvxCqxwFre4vbpeTlKbN1T6rc+APDCevW9+68f5UKRkULMbosGHKyUX8avPm/JLmcmw4YNw7Bhw8S/i4+PL3XbBQsWWP+AiIiIiCqBXU7UiIiIyH4ZHGGVZrUGRyscTBXHiRoRERFZhl992gyz+IiIiIjsFO+oXXM57TIMLjwdd7K2g9Wu8QCgv3iZ9UVlvCzGvzuuJpw3yShUYoZ7e4jb7z+2WolV0ymeianeUIn5LV4mjp0lRoV9rvxBjI8yc/vbTZRO8cVwIfb6xnPi2MnlPAa9wgHJylEHyvlot5cl/mrhQGTSv5TY31qgEgOA3fdPV2L1Osurd9TsEabE/t1cbtDefWqeEgusbhTHJh+o5GKP6w1rrbEfKhXvqBEREZFFDAYrrfVpMH+iNnv2bDRv3hxeXl7w8vJCVFQUfv75Z93xCxYsuHqcJX5cXV1NxmiahnHjxiE4OBhubm6Ijo7GkSNHynxeKgInakRERGT3wsLCMGXKFOzatQs7d+5Ely5d0KtXLxw4oH9H2MvLC+fPny/+OXXqlMnfT5s2DZ988gnmzJmDbdu2wd3dHTExMcjNza3op2M2ftdHRERElrFyw9vMTNPmg9JyjyWXiwSAd999F7Nnz8bWrVvRpEkTcfcGg0FcghK4ejdtxowZeOutt9CrVy8AwJdffonAwECsXr0a/fr1K9NTsjZO1K7Jz84H8uVcgDtZi2Zq7E+1f6PNeQt9KDMyyrfPLRsr/zeoLd6finGpHWnfnLFKbFvKJnH7NcfUBp0vt5dzakJXfqfEnu1YWxwLnNSJm6rt7XrrQde0bi1/+O/adfu8P4c/ucfssZMHV35+WL+DTymxpY2/Lvd+GzVQY4cOl3u3on4/dFZihvu7imOXeL2txB76apsS+2TUMXF7Jyc19u9Ocj7bG81rKLGevyYLI4FDz7ZTYlnT5YbbwS1uTD6MVwog77HiWHutz5uXfBw/fjzeeecd3e2KioqwfPly5OTkiEtMXpednY06derAaDSiVatWeO+994ondSdOnEBSUhKio6OLx3t7e6N9+/bYsmULJ2pEREREAHD69Gl4eXkV//nmu2nXJSQkICoqCrm5ufDw8MCqVavQuHFjcWyDBg0wf/58NG/eHBkZGfjggw/QoUMHHDhwAGFhYUhKSgKA4pWPrgsMDCz+O3vAiRoRERFZxspVn9cLBG6lQYMG2Lt3LzIyMrBixQoMHDgQGzduFCdrUVFRJnfbOnTogEaNGmHu3LmYNGlS+Y/dRlhMQERERJa5PlGzxo8FnJ2dERkZidatWyM2NhYtWrTAxx9/bNa2Tk5OuPvuu3H06FEAKM5dS042/eI4OTlZN6+tMnCiRkRERLclo9GIvDy1/5ykqKgICQkJCA6+mp8bERGBoKAgxMXFFY/JzMzEtm3bSs17szV+9UmlquzCgSdf9DV77KI5lyrwSMqu39bHxPjSe1aZvY/aZ/+pxALho8QGbJb7/+w6mqbEfiwoEsd2aqb+JvlBg/bi2B+Pq19VZNZVm9sWGTVxe8ntVDSgJ7qvmkAOAP6v3K/ELLkOKsyZiklFb/WA+v5ddNj892nHzFeU2CYvtdksACx9OF6JDX3vpDg25bNWSuzfZ9QGsqEh8nHdf/xDJfb8NPmuzsC/LyixyY/VF8dmnzilxLxC5a8Ds5NvNFXWctXm1xXN2sUE5hg7dix69OiB2rVrIysrC4sXL0Z8fDzWrVsHABgwYABCQ0MRG3u1ofHEiRNxzz33IDIyEunp6Xj//fdx6tQpPP/881cf22DAiBEjMHnyZNSvXx8RERF4++23ERISgt69e5f7uVkLJ2pERERkmUpYmSAlJQUDBgzA+fPn4e3tjebNm2PdunV48MEHAQCJiYlwcLjxReGlS5cwePBgJCUlwdfXF61bt8bmzZtN8tlGjx6NnJwcvPDCC0hPT0fHjh2xdu1apTFuZeJEjYiIiOzevHnzSv37+Ph4kz9Pnz4d06fLd2CvMxgMmDhxIiZOnFjew6swnKgRERGRZQwOgIMV0twNTJW/FU7UiIiIyCIGRwMMVvjq0xr7qOo4UbvGI8ADBteSp8M+E9PtgV6Cf0Uk89trgYCeokNqJ/SljcqfLN76v3uV2IRuagL4+vVyJ/Ua9fyUmJuvmzh2VaNGSqzIX16ZoLmbmsQsrY3wfc8nxe2XYLsYt0e9XwsX46s/OKnEfll2Ud7JMvVaeKC3sMwGgA2ry7nUhgWWdpO730v6nxysxJaEfy6OLe/7N3Du/8q1/aw3TorxR79V1/qY+8IZJfbkHLmR6vY+E5RYdm35n9OVr6iFOA//niqOddomv39vKd/2xQRkO5yoERERkWUcDFd/rLEfKhUnakRERGSZSqj6vFMxi4+IiIjITvGOGhEREVmkMhre3qk4UbvG1dcVDq5OlX0YdmfAy2qH9UWf6iRK30ECA+R4cqM4JdZv5z/EsUvbrFBiPfPeFccGvDtbiQ0tMr/bv7FI7fbfsY6POPb/zqoJzaEZJ8Wx3f4Vb9bjrw0YbtY4eyYVDejRex1/dHlTidmyaKD/OZ3XIaihElriMEQcKhUO3JM+VBzbdMq3Six+xANKrNncneL2Ti2kpQEOiGNf+fguJTZ9+N/i2A87NVNi3tmdlVjym1+I29ep66zEhj6mFuEAwITN55TY5UF/imPd3wpVYg7V5C++clJziv9bczTA/E8DK3F0uPpjjf1QqXiGiIiIiOwU76gRERGRZRxhpWKC8u+iquMdNSIiIiI7xTtqREREZBGDwUrFBAYWE9wKJ2rXuLo6wcGNxQQ3SzxZoMTibX8Ydic5xfyxBn95JQeJ+4o1Yvz0G/9WYgPX/aDEIlpLyddARtoVJbZ2u9qJHQAyendQYpML5Cc8flo7Jfavx9TVBmK+7SFuv7TLz2L8dicVDVjKkhUAJJFJ/1JiBf51xbHV/vpDifXb+pg4dnMt9XMy4oqaXA8A674+r8SOTlmsxsStAUAuBpAkPdVHia18SC5SuMvnbiUWPONjJZY/fZL8YFcylVCtrxaKQ7uE+yix/lfeF8cOGD1FiRUVqIVA6iCblxKwj5oN8atPIiIiIjvFO2pERERkGS4hZTOcqBEREZFFDI4GGKzwtaU19lHV8atPIiIiIjvFO2rXZF28DIMrT8fN4r9Xk2ZvN/Ui1NixE+Xb5z8XqUn0APDNk2oivSUJ4A7B6koQANBo3iIltupxNSE6etZv4vbuNd2VmKbJCcgRO9XO7846v/WePaKuUvHd388osY+zT4nbB4pR+5Szv4sYd2/6qxLrd/ApcWyN1ZuU2Lx/qqsCAMAet1wLjk51NkJI2r+ixgCg3+ZeSqxvWrI49rF7tiqxVDf5GK6oNSwW6X/mZSX21ql94lgt9bQSy0OhOPZgmlpkcPSvHCXm8NIb4va7JjysxGpWl4vRpt3XSYktcRsljvX9MFKJZZyRV65wdr9RwKHlFeKyOKoCOThc/bHGfqhUnJkQERGRZZijZjOcyhIRERHZKd5RIyIiIsvwq0+b4UTtmowzGYAzT0dVVN58NMl7kdXFuJphYhlD50fF+JGOaq6g35gPlJhPbR9xeynPJS8rXxzrU0N9bmkX5AyYnaPURrZLa8xXYoOeCxK3/0mMVox+v6l5RQCw9H61cbBEykXTkzh0pRiftUFN2nLu11Qc23H6L0rsv2YfAdBrl5on13pngjy4g9po+atJDcShLvlqY9hz+XLz5I0ecmNXc730914ldkjnWlx675dKrP/2x8WxhmC18e+va9TmvEVfPygf2JF0JXQmVc1xA4Anf1qvxL4dHCyOffp4mhLzCvUSx7r73XifGq8UMEetCuMZIiIiIrJTvIVEREREljFYqZiAa33eEidqREREZBl+9WkzPENEREREdop31HS88vFdYnz68L9tfCRkj6Z9f0SMf2bBPnoKCcWH09VGnAAQs0JtMlpwRW3m6ejsKG6vVzggSUvOVmIZZ+TGx4182yqxPw1qMYFmlJvr2pLz8i1iXE1BB+5uocb2/Cnvd/3/7lViDy07Jo7t9+EjSuw3J6M49r9T1OR2Syxt/LUSk9usAv/3fj0l1r9/N3mwo/rPRohzmDi0QX015rtjqBI7mSk/13nTf1dicctTxbFtCj5UYkudXhXH9pmnNmCOftxXiRV0lYt7vnFUG/GmnBsujr3/N/U5vPS40IUbgHP8cSXm6CS/p8/uLXHO8uXGvhWKd9RshhM1IiIisgwb3toMp7JEREREdop31IiIiMgyDgYrffXJO2q3wokaERERWYY5ajbDido1fvX84ODqVPzn48dzxXFq/+6qof8ZNTkWAJaEfaqOPa0mAwPAklqzzNqvtM/bzaXagWL88AU1AXuf/xfi2K0r1QTqbnPbiGNP9lGTtX1TFiixK5fUzvd6QlvK3dH93NSPhQSdYoJ1iWuVmLOzOq5Bc7m7evJJNVl7Sfjn4liv4+rKAj197hbHxjeepMS+/PSiOLZ/kpBw7q2upLDHTU7Ff7DbH0rsZ52bBNq8b+S/EIz9rIkSi33hgBJrmPy0uP1fgV8psf6n/i0/WJ25Sih3RLg41Pf1iUps/vvJ4thla9orsez125TYr3Fy8cWiOZeU2OMfyut/1F+hFk+kzpNXfRh8zLxCDaloAAB65r2rxGpMl9eNcHJzUmJns/LEsUX5RUqs4EqBOLZGPb/i/zbmFkA9U1RVcKJGRERElmExgc1wokZERESW4VefNsMzRERERGSnOFEjIiIiy1y/o2aNHzPNnj0bzZs3h5eXF7y8vBAVFYWff/5Zd/znn3+O++67D76+vvD19UV0dDS2b99uMuaZZ56BwWAw+enevXuZT0tF4Fef16QdSwOcb5yONUISa1VmSYK/VDSgZ0c1OYHbXP3zP5aPwVnuAm4rjkGeYlyvcEASFqrGDqRtV4MA6n+hxqVu/5nnssTtnd3VhOactMvi2Ixc87ucvywkgX/ipo5LfvEFcfvEgjNmP1Zm3R+U2BKoMUBe57n3GLkbfILjBSU2a7N6vjvpHNfiVe2U2LbjaeLYMZ1rKbFXIzvLO/Yer4T+MUtdMmF1RpLOkamWCEUDgLwSg2tWujhWKhxonDJAHDujj1o8UbeReoH41PYWt3+s4C01Jo4EtpxXizr6LNkrjnXxclFiISWS86/zGq2uOgEAXZcvV2I9WsjFORtOqv+WZKbLxWrSaiMFV+T3dM0G/jf+UM3291yuT2qssR9zhYWFYcqUKahfvz40TcPChQvRq1cv7NmzB02aqMU38fHx6N+/Pzp06ABXV1dMnToV3bp1w4EDBxAaeuMDuHv37vjiixuf3S4u6vVRmThRIyIiokqVmWlaWe7i4qJMmB55xHQJtnfffRezZ8/G1q1bxYnaokWLTP783//+FytXrkRcXBwGDLjxy4WLiwuCgtRKb3vBrz6JiIjIMgYrfe1puDoNqVWrFry9vYt/YmNjS334oqIiLF26FDk5OYiKijLrkC9fvoyCggL4+ZnePY2Pj0dAQAAaNGiAIUOG4OLF8n0TZG28o0ZERESWsXLV5+nTp+HldaPfot7XjwkJCYiKikJubi48PDywatUqNG7c2KyHGjNmDEJCQhAdHV0c6969Ox5//HFERETg2LFjeOONN9CjRw9s2bIFjo6O5Xhi1sOJGhEREVWq6wUCt9KgQQPs3bsXGRkZWLFiBQYOHIiNGzfecrI2ZcoULF26FPHx8XB1dS2O9+vXr/i/mzVrhubNm6NevXqIj49H165dy/6ErIgTtWt8I3xNViYA+zwDAO7PUru2/+b5odnbvxr/lxIbYsHjV3bRgJ6lj24s9z7qv9BciSU5+8iDHdWE27Ba6liPejXEzRPT1RULnJ3k3xYb+1dXYpv3y53nG/ipY2M2P6XEVp75Rdx+y3n1uFqLI2V9Pmslxo880VKJ/dl6vji2pYv6MTg9T03qPnuP/HHZ4ZMEJRbRwFUYCYS8elSJTdmhFoUAwICeasHKiqF/KrF/fKpeRwBQ7eggJZY7T75uCy4IK1o4yc/h/96vp8R2ufqKY//YKCTNC8UESa4e4vYnsg4qsYdWbhXH1vZWj3dsdB1x7H92pyixs0fUr7seaqQ+VwD4p/B+GDlFXu1g8YvquZGKe/T415ff0zmpOcX/rQnXa4WrpIa3zs7OiIy8ujpF69atsWPHDnz88ceYO1culAGADz74AFOmTMEvv/yC5s3l98t1devWhb+/P44ePcqJGhEREd2m7KThrdFoRF6evCQXAEybNg3vvvsu1q1bhzZt5CX6Sjpz5gwuXryI4GC5ircycKJGREREdm/s2LHo0aMHateujaysLCxevBjx8fFYt24dAGDAgAEIDQ0tLkSYOnUqxo0bh8WLFyM8PBxJSVdb2Xh4eMDDwwPZ2dmYMGECnnjiCQQFBeHYsWMYPXo0IiMjERMTU2nP82acqBEREZFlKuGrz5SUFAwYMADnz5+Ht7c3mjdvjnXr1uHBBx8EACQmJsKhxB262bNnIz8/H//4xz9M9jN+/Hi88847cHR0xL59+7Bw4UKkp6cjJCQE3bp1w6RJk+yql5pB0zQ5QeIOkZmZCW9vb1R7qT0MJXJVFkxPrcSjqjqSdz+gxAJbbaiEI7Gu6kd7iPHLkfpdsm/2j0K1ma+Tg7M4domDmtn3pJD74hkk5/pkJWWbfVySoGaBYjwpQc3VMX4wWon5zpgjbp+XpX5lkZIl5879MVr92iItfI04tlEDNdZijdyUNe/rzUps1WQ1l6y/cba4vfTajPxUOAAAly+qTYaTDUKHYADOb6v5mScy9ysxR4P8+3ZWfqYSu39uvDjWQWiYeulkujjW0Ukd26CV0L0ZwJuD9ikx6bpdpNNgXBpb9Kz6mQIANX7ZrcSc3ORcsLNC0noDo5pP92QTfyUGAJO/VJ9XQKOa4lj36uoxnNh1Thwr0esHW7Phjccz5hbgwph1yMjIMCshvzyu/5uZvnUsvDzkPEaL9pedC597Ym1y7Lcr9lEjIiIislP86pOIiIgsYyfFBHcCTtSIiIjIMpXUnuNOVOapbEZGBl544QVERkaiUaNGOH9e7iFDRERERGVT5jtqQ4cOxbFjxzBt2jQ89dRTuHLlasPEV155BfXq1cOwYcOsdpC24BnoCYNrydPBYgJrCKheNW9rW1I0oOffv36jxAY1DhHHBgvrBUe0VsdakqSsJ7KtnBgucfFUix+mHFqnxApz5Yaczu7q9vnvqI1aASDNbYIS658zVRy7xH2MEgsKk/sibRAKByQf7lFfLwD4P6Hh7FiXInkf/e5SYi5H5bGGlONKrFHsciXWql0tcfvjSVlKrHUDOeH917hjSszVW656C7tLTbA/uO20OPb3X+9TYi8LHwnBq38Xt5dMLJLXYVz5lNr8uOt7cuGSu1u6EgsQzk1ekfm1ds+3ka+vx+qFKbH7j6WJY6XaPgdH+TPUWGgU/9tm+NWnzZT5DP3888/4z3/+g8cff9xkPayYmBgsXLiwXAc1a9YshIeHw9XVFe3bt8f27dt1x3777bdo06YNfHx84O7ujpYtW+Krr74q1+MTERFRKay8KDvpK/MZ0jQNnp7qEif169fHkSNHynxAy5Ytw8iRIzF+/Hjs3r0bLVq0QExMDFJS1CU/AMDPzw9vvvkmtmzZgn379mHQoEEYNGhQcQM8IiIiottVmSdqPXr0wKJFi5R4Tk4ODHqNX8zw0UcfYfDgwRg0aBAaN26MOXPmoHr16pg/X16nr3PnznjsscfQqFEj1KtXD8OHD0fz5s2xadOmMh8DERERleJ6MYE1fqhUZc5Ri42NLV43S9M0GAwG5ObmYtKkSWjVSl4o+Vby8/Oxa9cujB07tjjm4OCA6OhobNmy5Zbba5qGX3/9FYcPH8bUqXLuSl5ensm6YJmZalNIIiIiKgVz1GymzBO12rVrY/PmzRg6dCguX76Mdu3aISsrC15eXvjpp5/KtM8LFy6gqKgIgYGmXdADAwPx119/6W6XkZGB0NBQ5OXlwdHREf/5z3+Kl5S4WWxsLCZMUJOS8y/nw1BUCQmZlaDnYDXp9cfPK6ZqN7i6txJLqpBHuv3Mi2yoxIKW/yaOPTkwQoldPK8mi1vD0R1nlZjeygR5WflKrGd4HSX2obecbH5RSKpu/NkScey+Pn5KrOk36l19AHhTiG3wkH95e212IyV29tkXlNhbO1eL27f3Vu8IdKypXvcAYGgYp8TW+YhDcW+/v5VYIdTCg/0H1NUhAKCaq/rxLhUN6PEMUlNbAOCc8Jpte0deqWP8ZjUNxllIjm9xQv1MBgDnt2YpsQkL1VUBAHlVjnVjO4ljn159UImdT1A/meYLK2foGdbiHjE+88+tSuxKuroKAgB4hcjnXJJxJqP4v7U8uViHqoZy9VGLjIzEunXrkJiYiD///BNOTk5o3749fH3VZT8qkqenJ/bu3Yvs7GzExcVh5MiRqFu3Ljp37qyMHTt2LEaOHFn858zMTNSqJVdNERERkcBgpUIAFhPcklUa3tauXRu1a9cu9378/f3h6OiI5GTT3xCTk5MRFCT0J7jGwcEBkZGRAICWLVvi0KFDiI2NFSdqLi4udrXYKhER0W2HE7VSpaWlwcfHx2SR+LKyqzPk7OyM1q1bIy7uxtcDRqMRcXFxiIqKMns/RqPRJA+NiIiIqCIdPHgQU6ZMQYcOHVCzZk0EBARgwIABWLlyJXJycsq8X7uaqAHAyJEj8fnnn2PhwoU4dOgQhgwZgpycHAwadLUJ5oABA0yKDWJjY7F+/XocP34chw4dwocffoivvvoKTz31VGU9BSIioqrNGj3UrFWQUIkOHz6MV199FfXr18c999yDHTt24MUXX0RycjJ++ukn1KlTBxMnToS/vz969OiB2bNnW/wYdrfWZ9++fZGamopx48YhKSkJLVu2xNq1a4sLDBITE01uJebk5OCll17CmTNn4ObmhoYNG+Lrr79G3759LXrcnNQcwNnuTkeFqKjCAcnBtEtKTE0Jr9r6G+U35rO/fK3ENKPcCd21k1pMkPndHrOPwc3HVYnpJTTXqKe+Qo0D1ERtAEiCmsjeZYHaGkcqGgCA6n5uSqxVLTkRP265mlz/5nJ5v5KPvm4pxs+0UVcWWOLyihL7+rMm4vaJu9XVIEbNUa97PZfS5bjrTHV1Bdc3Y5WYVDQAADWC1cT0zHNyAUrj9mqe7pF98ufEZ4PV85Wed1kcu/OEeh5SXnlViX1xaIW4vVTQoHctudd0V2KXC+RvVlIOqSvPSKts6D2W5JHVcu/OHdFdldjq9vL1Ia3w4OAot68wllw1Ib8SigkMBit99Xl7t+fYvHkzcnJy8Mknn6Br165wdr5xHfn7+6Ndu3aYNGkSTp48iTVr1uDbb7/FkCFDLHqMMs9MBg4ciOeeew73339/WXeha9iwYbpLUMXHx5v8efLkyZg8ebLVj4GIiIioNIMGDUKvXr3g51f6LYjw8HAMHz4cw4cPt/gxyrUoe3R0NOrXr4/33nsPZ8+qJf1ERERUBV0vJrDGz20uKioKJ06cqLD9l/kMrV69GmfPnsWQIUOwbNkyhIeHo0ePHlixYgUKCgqseYxERERkTzhRK/bAAw/gnnvuKXVd8vIo1xmqWbMmRo4ciT///BPbtm1DZGQknn76aYSEhOCVV14p15qfRERERPZuzpw5GDFiBLp27Yo1a9ZYff9WyZ4/f/481q9fj/Xr18PR0REPPfQQEhIS0LhxY0ybNg2vvKIm5tKdoa63moTe47x8PSwJnl7Rh1MpljjIiaPzr7yvxPa0kLuuI8NRCdWod0qJ6SU/O1Qz/3cyaR97LFi149JJNVHa1VvuXXg57YoS26HzHJ4WYv32ykVDI9LVBP+jmxLFsbWzdyqxacK4E3XDxO2r7VEfK6qTWrwBAJ9MbKfElh+6II79/Tc1wd7RSb0OspOzxe2lwgG9FSZOHlGPIbhRgDj2rd/UIoOze3eLY5eNbKPE7l32mRL73xP9xO0H9T2pxBzeWyqOTTuuXjdD5Px+BDZRn1t6YroS8whQCxQAwNldLTz4+qHW4tjfL6vX3YnDajEDADRop15j2fnqahQAcDn9xntHyy1EujiqAnEJKRNjx45F7dq10b9/f0ydOhUvv/yy1fZd5olaQUEBvvvuO3zxxRf43//+h+bNm2PEiBH417/+BS8vLwDAqlWr8Oyzz3KiRkREVJWw4a3iySefhJ+fHx599FGsWLEC7du3R+vWrdGqVSvUr1+/zPst80QtODgYRqMR/fv3x/bt29GyZUtlzAMPPAAfH58yHxwRERGRvUtPT8fMmTMxc+ZM1KxZE2FhYfj5558xffp0FBUVwdPTExkZGbfekaDME7Xp06ejT58+cHWVb/EDgI+PT4VWQhAREVEl4B21YiNGjMD8+fPh6+uLt99+G88//3zxUpVXrlzB3r17sWeP+X0vb1bmiVqnTp3ENTM1TcPp06etsvanLdVtFQIHN6cbAQsaVpK+HmHdlNgSJ+t9d29v/rlIzUHKeLyHOPbFzd8psScbyGvaGup1VmKB/mpekF6OmkegmiuYmyE3vJUaqD7cMlgc+4u3+otafna+ErtySc1F0+Nfo7oYT979gBKL95MrzOP/VH9z/eX5juLYZov/VGIrhXFLo+WEp3e2dVZiAV8fE8e27fSbEptSKOdmeo+dosRef7yhEvvwZ/mxpObJmWczxbFSrmCiEAOAyLahSuyZxxuLY/+Rpl53I9LPKLGXfpUTsGt5Oikx7zAvcezli2rT3aQEtSEzAHTpWk+J/XogRYlJOYEAkJ+jXuMd58WLY/8c8rgSK8yTxyb+reYKFlyRr/HCvBK5a5XS8JYTteu+//57fPTRRxg4cCCcnEyvWTc3N0RFRVm0DObNyjxRi4iIwPnz5xEQYJqUmZaWhoiICBQVyQmQRERERFXF33//DUdHeVJvDWWeymqaBoOw9EN2dnapX4cSERHR7c5aPdRu7ztqSUlJKCw0/47m8ePHLX4Mi++ojRw5EgBgMBjw9ttvo3r1G19TFBUVYdu2bWJhAREREVURbM8BAFixYgXGjBmDbt264dFHH8XDDz+MmjVrmozZtm0b1qxZgzVr1iAxMRFZWfKau3osnqhdT4jTNA0JCQkmC5A6OzujRYsWeO211yzdLREREdFtZdiwYejevTu+++47LFiwAC+++CLatm2Lhx56CCdOnMAPP/wAAOjZsyemTJmCBx980OLHMGiapmacmmHQoEH4+OOPi3um3a4yMzPh7e0N5/+LgsHlxrx1/vtyEqotpe5Rk6dr3r2hEo6k7N7/soUSGzVATd6uKqQ0heEzGohjZ3YPV2Kf7bsojq3tpaYTLPzhLyVWI7KGuH1eVp4SCw/zFsdeKVSb29bWaVj7xy612atvbR8lduGY/Lyc3NRkcc9gT3Hsmg8OKbEjch49jgoJ/t8dSRfHpl5Wk7V/XfC3EpsZKycD70tRk9if66M20QWAQ5s7KbHPdyWJY6sJiex5QhK7JVyERq0AUCQ0NJaKEQAg5aCadN//0Ubi2K9btFViDhO/LO0QTex45yEl1vadn8Sx1f3clJhUJAHIDW+LhMayUtEAAOSk5igxN1/18fXG+t/lL45NPawWE+gVTxTm3vi6TcsrxOX3f0dGRkaF/5t8/d/MjMT/wstLLvyxbH+X4V37eZscuy1cvHgRP/zwA3766SeEh4ejV69eiIqKElPFzFXmYoIvvviizA9KREREtzFWfYpq1KiBgQMHYuDAgVbbp0UTtZEjR2LSpElwd3cvzlXT89FHH5XrwIiIiIjudBZN1Pbs2YOCgoLi/yYiIqI7EO+o2YxFE7UNGzaI/01ERER3EE7UbKbMOWqxsbEIDAzEs88+axKfP38+UlNTMWbMmHIfnC25eLjAIHRkN8eClW3E+DNPyAnF5uoZoXYh347ba4K8/NEOSmw7qm4xQdSlV5TY4vRT4tieszYrsbFC53kAeLphMyW2fEuiEksWuqvrOSIk0QNAzgU1Ob5bv6bi2F3CygQSjwC1Q72emQ/WEeOnhfg/wuVVHxyED/92gb+IYx+aqq4WsG2zem4a+sqfD2v+VhPW/+99tfM9AGStVAsiHKrJ/1AtGXy3Envh+6NK7NJJeRUVk871t+Dmo76OV9LllSu+H32vEnvy633iWJ8d6ioE7v5qAvruV9WiAQBoMHaFEqvZQE7El86jXjHB8X8/r8TCPvqPEtNbUcOvrp9Zjw8AhXlqj63IIPn9kHZcXVkk44y8moRHgHuJBy97ojrZvzJPZefOnYuGDdV/VJo0aYI5c+aU66CIiIjIjl3vo2aNHzPNnj0bzZs3h5eXF7y8vBAVFYWff/651G2WL1+Ohg0bwtXVFc2aNcNPP5lWDWuahnHjxiE4OBhubm6Ijo7GkSNHynRKKkqZJ2pJSUkIDlbX/6tZsybOnz9froMiIiIiO2aNVQks/Po0LCwMU6ZMwa5du7Bz50506dIFvXr1woEDB8TxmzdvRv/+/fHcc89hz5496N27N3r37o39+/cXj5k2bRo++eQTzJkzB9u2bYO7uztiYmKQmyvfUTbHhQsXcOGC2mqlrMo8UatVqxb++OMPJf7HH38gJCSkXAdFREREVNIjjzyChx56CPXr18ddd92Fd999Fx4eHti6das4/uOPP0b37t0xatQoNGrUCJMmTUKrVq0wc+ZMAFfvps2YMQNvvfUWevXqhebNm+PLL7/EuXPnsHr1aouOLT09HUOHDoW/vz8CAwMRGBgIf39/DBs2DOnp6eV63mXOURs8eDBGjBiBgoICdOnSBQAQFxeH0aNH49VXXy3XQREREZEds3IxQWamaS6ei4sLXFzkRtvA1SUrly9fjpycHERFyc2ot2zZorQSi4mJKZ6EnThxAklJSYiOji7+e29vb7Rv3x5btmxBv379zHoKaWlpiIqKwtmzZ/Hkk0+iUaOrDaAPHjyIBQsWIC4uDps3b4avr69Z+7tZmSdqo0aNwsWLF/HSSy8hP/9q92ZXV1eMGTMGY8eOLetuK01WUhbgfON0PPF+E3HcylHqLdbyFg3oWfa3mngcUSGPVHESMyt/hQdbCqxeW4n1+zFeHPvJ042VWHa+3A0+K19NKJa6+ktJ4YCcGO7sIXepd3RWO+J/unS/MBLw1EmKVo5Lp+jg7F41TSI3cq04duSn6goPDf8lF6bsu6AWWozZKKdk1GsTqsTe/1J9HXelqOcbAF4UVmd45nH1tQWAn4WCpZFRagoJAPRyUo+h14tdlFithXLz8cICtZhAr9hEr3BAEu5VU4llnjN/7cIG7cKU2MazOktMCDLOZIjx/By1AMQk4b6Eep/PU2KuwjV66WS6uL20aoO0AgEAVHNRX/O4fzwljq19brYSyzwnFxNkp5R4vHzzFwW3GitP1GrVqmUSHj9+PN555x1leEJCAqKiopCbmwsPDw+sWrUKjRvL77ekpCQEBgaaxAIDA5GUlFT899djemPMMXHiRDg7O+PYsWPKviZOnIhu3bph4sSJmD59utn7LKnMEzWDwYCpU6fi7bffxqFDh+Dm5ob69euXOgMmIiIiutnp06dNlpDSm0s0aNAAe/fuRUZGBlasWIGBAwdi48aNupM1W1i9ejXmzp2rTNIAICgoCNOmTcOLL75o+4nadR4eHmjbVl3PjYiIiKooCys2S90PUFzJeSvOzs6IjIwEALRu3Ro7duzAxx9/jLlz5ypjg4KCkJxs+q1OcnIygoKCiv/+eqxkcWRycjJatmxp9lM4f/48mjSRv4UDgKZNm1p0h+5mXEKKiIiILGMwWOmrz/L1gDMajcjLyxP/LioqCnFxcRgxYkRxbP369cU5bREREQgKCkJcXFzxxCwzMxPbtm3DkCFDzD4Gf39/nDx5EmFh6tf6wNVcOD8/tfeeuSpkCanyrBJPREREdLOxY8eiR48eqF27NrKysrB48WLEx8dj3bp1AIABAwYgNDQUsbGxAIDhw4ejU6dO+PDDD9GzZ08sXboUO3fuxGeffQbg6lxlxIgRmDx5MurXr4+IiAi8/fbbCAkJQe/evc0+rpiYGLz55ptYv349nJ1Nc3/z8vLw9ttvo3v37mV+3lxCSodjoNo929b+b4HadO/7SjiO8mhZs4USW4tvK+FITPX7+xkltvSuBeXe7+Ttq5XY1z3U1RkAoM2cn5RY16ZqjgMAxG5UVzHITslWYnlZ+eL2gU0ClFjmWTlJ2am6mjT/2EN3iWPXblaT9gtz1cTmtBNy93yJXlf/i0Ii/Ee7/xbHPtUwSImlHJMLInIz1N/Ga7dSWwxdWrBb3D74XvWxNp5KF8dKne6b1vAUxwatVj9jDQ7xSkwvid0k2fwWvMPUr5w+fSJSHPvFQTXx3zfcRxzr4qnmGR3erq5W8IIQA+Rilawk9boH5BULpE7/ALBskLrqQ7+Fe8Wxkrws9ZqR3jcAkCsUasxJ+EEcK+1DKpIAAAfHGzdENEcD5DKkClQJS0ilpKRgwIABOH/+PLy9vdG8eXOsW7cODz74IAAgMTERDiW+ju3QoQMWL16Mt956C2+88Qbq16+P1atXo2nTGyutjB49Gjk5OXjhhReQnp6Ojh07Yu3atXB1NW/VFeBqwUCbNm1Qv359DB06FA0bNoSmaTh06BD+85//IC8vD1999ZXZ+7tZmXLUCgoK0L17d8yZMwf169cv84MTERHRbagSJmrz5qnVuiXFx8crsT59+qBPnz76D28wYOLEiZg4caLZx3GzsLAwbNmyBS+99BLGjh0LTdOK9/3ggw9i5syZSlWrJco0UXNycsK+ffLabkRERER3koiICPz888+4dOlS8RJUkZGR5cpNu67M0+GnnnrqlrNbIiIiqoIqYQmp24Gvry/atWuHdu3aWWWSBpSjPUdhYSHmz5+PX375Ba1bt4a7u2ljQVZ9EhERVU2a4eqPNfZzu3NwcLhlEaXBYEBhYdkaE5d5orZ//360atUKAPD336YJvbdj1WfdViFwKNHpPfnxzvLAATtsc0AAvv/PWZs9VkXxLZK735vryRflJTcWzVGT0/v9NUAcu7Thl0qs2R9qYnjarIbi9h8O/UuJte8gJw7/mKEm/rb4aI041uCgvk/OCknKANC9kdoN/mBNtev630cvits7VFN/a/Wu5S2OTUpQV5P4OUcuUnD3V4/BXejwnrhb7d4PAI/2UIsUvvtZLhCQzFspL8a8yPuoEpOKBgBg3sutlNiao2rC+iM95Ws5UyhyKPB1E8f6BKmFA90vyWPzhXO+/Ck1Cf7B9+LF7V081ePVKzaRChKGLFKvewC4Wyh4KbgsJ7zrdfY3V8EVdb/+9WuIY52FlTqKCozi2Gk71OvRI1AtXJDeo4C8MkFRvroSBAAYi9Rj+OuS/A92XqZ6jfpFyJ+B1UqscmHMLYD1lgAnS61atUr377Zs2YJPPvkERqN8LZqjzBO1hQsXIiwszKTCAri6yOnp06fLfEBERERk3zTNCE0r++Sj5H5ud7169VJihw8fxuuvv47vv/8eTz75ZLmKFcr85XBERAQuXFDn8GlpaYiIuN1WpCQiIiJzGTWj1X6qknPnzmHw4MFo1qwZCgsLsXfvXixcuBB16tQp8z7LPFG7Xn56s+zsbIv6jxARERHdzjIyMjBmzBhERkbiwIEDiIuLw/fff2/Ss62sLP7q8/rSUQaDAePGjUP16jcawxYVFWHbtm0WrZFlL47vPgc43zgdvn+vqMSjqTriI8eWa3spF02PlIumJ+HuRkrs1HA5l2yLEDv7TW9x7PIP45WYlM8CAJ7Bar5SK6HBJwA8JDQU/VTIC7pSR85nSbus5ibpNQOV6OV3SQ1NpXw0V295geXVDzysxN4LjhPHjv8qQYnp5SB1bq/2LNp9OkMce5ePmvM0/G41fy/MU86NanN4rXBccr6So5DydKGB3IvymSx1bcC5+84rMTcf+RdjKb/Lp7acl+jo5KjEUhrJfZ8izqUqMb3muh4Bag6jlAuWofPaXBGaxepdi05u5v9z9lEndQHv+z5WrztXId8SkBsXS+9nAAir5aPENiXKz1fKS9Q7tyVz17Rc+XqrSBqM0GCFrz6tsI/KNm3aNEydOhVBQUFYsmSJ+FVoeVg8Ubu+dJSmaUhISDBZLsHZ2RktWrTAa6+9Zr0jJCIiIrti1DSrfG1p1Pl27nby+uuvw83NDZGRkVi4cCEWLlwojvv227KtymPxRO360lGDBg3Cxx9/bNZq90RERERV0YABAyq020WZqz6/+OILax4HERER3Sb41ecNCxYsqND9l3miBgBxcXGIi4tDSkqK0iNk/vz55TowIiIisk/WqtisalWfFaHME7UJEyYUrxgfHBx8Wza5Lcm3ji8MJRoIuraXm59i6gkbHZH9eqC3nJC8YbWaIHtezYeuMK3SnhPju/3Upc5yG7dRYlt/WyZuf290dSUWPvkXs4+rU5e6Ynzjr8eVWEHbMHHs4UtqA9bfhaR9p+pyI14pWbtmQ7WJLgC0CFPTGXYekRvpSsUE3gFqsnhNneMat189j3O2yI2e3YUGv1JSNwCs/Z/a8FZKbAeAe/3aKjGHV95TYnqNR7OS1NdGj1RY4v/HdnHssmNq0v7ZR6KVmMMPh8XtazbwV2Kph+W2qO3uC1dihof6imMvTVTPjfRYgPx884Smzo7OajEDAES0DlFip/aqBRUAENBAvZ6TD6nNiAFg/sGTSkxqCp2VlCVuX0do+psuFD4AwBGhAESPT20fJSYVXwA3NabOL1vHe7KOK1euIC4uDg8/fLU4auzYscjLu3GdOzo6YtKkSWXuiFHmidqcOXOwYMECPP3002XdBREREd2G2PD2hoULF+LHH38snqjNnDkTTZo0gZvb1VVH/vrrL4SEhOCVV14p0/7L3EctPz8fHTp0KOvmREREdJsyWvF/t7tFixbhhRdeMIktXrwYGzZswIYNG/D+++/jm2++KfP+yzxRe/7557F48eIyPzARERHR7e7o0aNo1qxZ8Z9dXV1Nltds164dDh48WOb9l/mrz9zcXHz22Wf45Zdf0Lx5czg5meagfPTRR2U+KCIiIrJf/OrzhvT0dJOctNRU0/xSo9Fo8veWKvNEbd++fcUrEOzfv9/k727HwoJLpy6ZrExg6BtaiUdj3wKfaS7/xerfy7Xfp4f6KbGvZsnd80fPUTuLTxOKBvSsdh6lxNpe+rc4dtLOA0rM4/eT4lipi/ih83JCsuTL/x0R413vqa3EAur4KLFMnYRmqcN6yiE1WR0A1gvxjp3l9XvTrqhJzId3q8UAl8PlRHxjhFqYInVnB+TE9ALh8QHAK0TtEq+XsH7Pt+o3A8kfvqTE3ti8Udx+mQXd5NOljvTddYoUNh1SYvf+vkmJ6X3cSoUDLp7Owkhg5+ZTSszh9zfkHQsCa8kFRieExH83XzclprcCwMP11c+Eb4vkBqkph9XrVnosAMjMUzv5V6+hFg0V5csd/4uEa/GCTsFNjXrqcwjRKWw5cUz9vNO7ljxLrGKi5RbC/JIW62DV5w1hYWHYv38/GjRoIP79vn37EBYmF4qZo8wTteuNb4mIiIjuVA899BDGjRuHnj17KpWdV65cwYQJE9CzZ88y779cfdSIiIjozsOGtze88cYb+Oabb9CgQQMMGzYMd911FwDg8OHDmDlzJgoLC/HGG+bfob5ZuSZqv//+O+bOnYtjx45hxYoVCA0NxVdffYWIiAh07NixPLsmIiIiO6VZ6avPqpCjFhgYiM2bN2PIkCF4/fXXoV1bv9RgMODBBx/Ef/7zHwQGqr33zFXmqs+VK1ciJiYGbm5u2LNnT3GiXEZGBt57T22ISERERFQVRUREYO3atUhNTcXWrVuxdetWpKamYu3atahbV256bq4y31GbPHky5syZgwEDBmDp0qXF8XvvvReTJ08u10FVBoOjAQbHG1m5bTftEMeNtNUB2bGlvctXNPDrevlu61cPqonSenKF7ubl1XbWWjGecSZTieklZUe2VYtQju6QO+2HtgxWYuf+lLuY/7rttBKrfZfaDf6ikIwMAEHN1N/mrugUHgQ2CVBim+LLtyJHyktyoca9q9VE/jcfkj/UPtmpdpmXCgwAIPOc+QUcHvVqKLHe3/2kxIb13yNu/930+kpMLwG8up+a3H6pUSNxbPZn65XYpmdilFhNqUAB8qoNBge58sCzrvnFF1KCvbOD/Du/tHKFtDKBtCoAALzYTD23X/wqX4vSc9NbNSJBeH3SE9OVmFRgAAD5QkGDk5v8z6m/sI/UbLlgZtXz6ioZD74XL46tbFe/+pSLLSzdT1Xi5+eHdu3aWXWfZb6jdvjwYdx///1K3NvbG+np6eU5JiIiIrJj16s+rfFzu3vooYeQkXHjF6YpU6aYzIMuXryIxo3VTgXmKvNELSgoCEePquvpbdq0qdy3+YiIiIhuB+vWrTPpk/bee+8hLe3GtxuFhYU4fFhek9ccZZ6oDR48GMOHD8e2bdtgMBhw7tw5LFq0CK+99hqGDBlS5gMiIiIi+3a94a01fm5314sH9P5cXmXOUXv99ddhNBrRtWtXXL58Gffffz9cXFzw2muv4eWXX7bmMRIREZEdsdY6nVVhrc+KVuaJmsFgwJtvvolRo0bh6NGjyM7ORuPGjeHh4XHrje2QVqRBK5Egevri5Uo8GvuRf7CrEnNuHCeOdReabecIOdVdLCga0PPJqGPl2n7i/GZKrGewmlANAIuFYgJfnU77UuGAu7+ckHxW6NruFyHvN+3EJSXWMlB9ryWFeYnbXxauZ2+dsckH1KR9ve73AY3VwoOUg+r24V8tELfPyVALGuboJFpnpaiJ4YV58soEwS2CzDouADgrJLe/d79aFBKW9C9x+9R3flZieonlucLzLTLKz0F6fT66dFyJ1awpd7l3E67n4yfV6wiQE/z9Q+Xr45IwtnWw/Ll/5nS6EpMKQOoIq2wAQCOD+jroFWpI9Ip+zgmFFu7CedRbmaBAuO6kwgkAuFKoTkRCdVZi2J2ivj5679Oc1BvnQdN5H5BtGAwGZUUma67QVOaJWmxsLAIDA/Hss8+aJMnNnz8fqampGDNmjFUOkIiIiOwL1/q8QdM0PPPMM3BxuTpZz83NxYsvvgj3a3cvyrPOJ1COidrcuXOxeLFaWt+kSRP069ePEzUiIqIqimt93jBgwACTO2hPPfWUOKasyjxRS0pKQnCw2geqZs2aOH9e7gVFREREVJUsWLCgQvdf5olarVq18McffyAiIsIk/scffyAkJKTcB1bZ9Bow3mkGJKrfs+dPlRt0fjvmkBLrt6+/EstbsVPcftXEI2Yf19D3wpXYov5q3hkApEd8r8QONo5UYg0OyI/vG+6jxDJOy01GG7QLU2LnhEaaAOBT21uJOXvIOTV9H2moxLxd1bevXp6MmBulk38j5cnp5UEVCdVNyULB0z8aqk1lAWDLWbUx7dksOUetrpAXeDpZbmgqvT5BTeQlXDKF/B5XRycl9ujyXeL2koIr5ucMLTq8WYxLuVxns9XX7PwZ+Vq0pOlvwayJSqzFl5+LY9OFxrIN/OTr1lXIxcoWXrMz5+VjPWpQ8wrdfOT8LoleU+fCXPX1cXZXn0N2tnx9Sa+Nm6/azBgACorUO0aplwvEsW8tOqDE6jSVr9v8ErmcmoPBCq1nLcO1Pm949tlnbznGYDBg3rx5Zdp/mSdqgwcPxogRI1BQUIAuXboAAOLi4jB69Gi8+uqrZd0tERER2Tl+9XnDggULUKdOHdx9991Wb80BlGOiNmrUKFy8eBEvvfQS8vOvzuxdXV0xZswYjB071moHSERERGSvhgwZgiVLluDEiRMYNGgQnnrqKfj5+Vlt/2X+fs9gMGDq1KnFC5D++eefSEtLw7hx46x2cERERGR/rn/1aY2f292sWbNw/vx5jB49Gt9//z1q1aqFf/7zn1i3bp1V7rCVOxHLw8MDbdu2RdOmTYtLU4mIiKjqMmqaldb6NH8iExsbi7Zt28LT0xMBAQHo3bv3LZdm6ty5c3Gfs5I/PXv2LB7zzDPPKH/fvXt3i86Hi4sL+vfvj/Xr1+PgwYNo0qQJXnrpJYSHh+vmOprLKn3USqoqfdSkBpB3Iq3bY2pwxydmb7+0+RIl1t84Wx48UV16rN+mR8Sh976jNt2t/exd4thLA9SmrDU3/qnEPh2jNhMFgIBE9Rw8+F68ODY5SU2K1ksy9vcSEq0L5JTgfCEhuX2Qmvz82fJUcXtJaEu1ahsALknFDzrFBM4O6u967z3XQt1nrvxbc8Ih9XhbCk10AWDHLqmZsHxcl9PUhqZeOg1ckxKSldgAoenunN5qAQoA9BEaBAc0qimOda+uFinEn5aba0sJ62v+vqjELCka0LPp3EYldqVQvhal49pyVn4OUlGWh9CouYbO9RWzQm2OrVcgIDU5vpKeJI6V7nLk56iveVhd+euro3vOKTG968vR2VE9rly5YMYrRN2H1EQbADyDbpxH62dF2aeNGzdi6NChaNu2LQoLC/HGG2+gW7duOHjwYHHPspt9++23xelZwNUF0lu0aIE+ffqYjOvevTu++OKL4j+X58aTg4MDDAYDNE1DUVH5yzzKfEdt7ty5aNhQrURr0qQJ5syZU66DmjVrFsLDw+Hq6or27dtj+/btumM///xz3HffffD19YWvry+io6NLHU9ERETlUxlrfa5duxbPPPMMmjRpghYtWmDBggVITEzErl36Fdl+fn4ICgoq/lm/fj2qV6+uTNRcXFxMxvn6yqvE6MnLy8OSJUvw4IMP4q677kJCQgJmzpyJxMTEcq/YVOaJWkX1UVu2bBlGjhyJ8ePHY/fu3WjRogViYmKQkiIv/xIfH4/+/ftjw4YN2LJlC2rVqoVu3brh7Fn5txAiIiIqH614tc/y/e96jlpmZqbJjznd/DMyrramsSRxf968eejXr59yBy4+Ph4BAQFo0KABhgwZgosX1bvXel566SUEBwdjypQpePjhh3H69GksX74cDz30EByEbx0sZXd91D766CMMHjwYgwYNAgDMmTMHP/74I+bPn4/XX39dGb9o0SKTP//3v//FypUrERcXV65OwERERGQbtWrVMvnz+PHj8c477+iONxqNGDFiBO699140bdrUrMfYvn079u/fr/Qz6969Ox5//HFERETg2LFjeOONN9CjRw9s2bIFjo7qV9c3mzNnDmrXro26deti48aN2LhRTSUArn4NWxZ21UctPz8fu3btMmnv4eDggOjoaGzZssWsfVy+fBkFBQW6M+y8vDyTmXpmprrgNhEREemz9lqfp0+fhpfXjRy9W+WIDR06FPv378emTWoeo5558+ahWbNmaNeunUm8X79+xf/drFkzNG/eHPXq1UN8fDy6du16y/3evISUtVVIHzXpzpc5Lly4gKKiIgQGmnZiDgwMxF9//WXWPsaMGYOQkBBER0eLfx8bG4sJEyYocRcvFxhcbpyOK5fUZOSqrIXc1B/LHIYqsfBz/YSRQPMhHZTYo6uEfEEHtWgAADr19FRix5rId2cDItSu/kuCPhTHDn5D3cclD/WxVohbA5O3Jur8japA6DgudTwHADcn9Za4n5v8lvRzU5PQfVzUmCXO7jU/RUFagQCQixz83dTn9WH8aXH7ds3UBPADQkEGAPgJid1671PvMDUpO18oENAbm3MhR32sQnm1ASfhNUsRiiQAoLqfWliSflFOxJe6+ksrPMw4KKeFWLI6wn7ha57awuMDQOI+NUH/oE4xgFR4IK2ecUFnhYkno2opsVm71ER+ALgsnEe9VQyk96SPEJOKgwDAO0z9/NHjV11Y8cBJp2hIKCYKbCIX1ySXLGLJN/+1tparVZ/lL2O4vg8vLy+TiVpphg0bhh9++AG//fYbwsLU1WAkOTk5WLp0KSZOVFfhuFndunXh7++Po0ePmjVRq+glpCqkj1pFzixLM2XKFCxduhSrVq2Cq6v8Bh07diwyMjKKf06flv8BISIiIvuhaRqGDRuGVatW4ddff1VSr0qzfPly5OXliQum3+zMmTO4ePGimIdfGcp8Rw0Afv/9d8ydOxfHjx/H8uXL4eLigq+++goRERHo2LGjxfvz9/eHo6MjkpNNy+WTk5MRFKT+5l3SBx98gClTpuCXX35B8+bNdce5uLiw3xsREVE5VMYSUkOHDsXixYuxZs0aeHp6Iinp6t1db29vuLldvVs9YMAAhIaGIjY21mTbefPmoXfv3qhRw/SudHZ2NiZMmIAnnngCQUFBOHbsGEaPHo3IyEjExMSU89lZR5nvqK1cuRIxMTFwc3PD7t27i/O+MjIy8N5775Vpn87OzmjdujXi4m70yDIajYiLi0NUVJTudtOmTcOkSZOwdu1atGnTpkyPTUREROYxQiv++rNcPxZ0gZs9ezYyMjLQuXNnBAcHF/8sW7aseExiYqLSeeLw4cPYtGkTnnvuOWWfjo6O2LdvHx599FHcddddeO6559C6dWv8/vvvdnNTp8x31CZPnow5c+ZgwIABWLp0aXH83nvvxeTJk8t8QCNHjsTAgQPRpk0btGvXDjNmzEBOTk5xFejNs+WpU6di3LhxWLx4McLDw4tn2B4eHuXuXUJERET2wZzlmOLj45VYgwYNdLd1c3PDunXryntoFarME7XDhw/j/vvvV+Le3t5IT08v8wH17dsXqampGDduHJKSktCyZUusXbu2uMAgMTHRpC/J7NmzkZ+fj3/84x8m+7lVae/N8jLzAOcbiZwunnICeFXgdfxhJdY47EFx7J/Ow5XYyZClwkjgwB+dlNiPMw8osex68nFt/FFN3H11sVzm/OZQtdnyC83lbvAf+ao3jlc8tVeJDZlYW9z+8h+nlFhEa7nIIUPoiK+XWN7iQfVErF9/TBy701v9ze6fL92jxPQSj1P/Uo/BWGT+b7JFQlI4AJwSChJ211OT/hvVkpOv9xxTk9gDAuRfsDyEDu9HdRLxpcKB0PpqIj4ApF1Q9+EkFG+M36TT5V44NyW7xpdkcFDzd++uJx/XIaGg4cej6eJYc0mFEwCw4m+1+t3DSW5L4C4UDrhVk8fmOwkrABSqX3W5+1UXt18Qp64W4hEgFy5kCwUJPrV9xLGFuWry/QUhJhUHAXJBxKWTl8Sx0soEUgwAmgnXzeY9Ze9LWpGur9Rpjf1Q6co8UQsKCsLRo0cRHh5uEt+0aRPq1q1broMaNmwYhg0bJv7dzbPlkydPluuxiIiIyDLWrvokfWXOURs8eDCGDx+Obdu2wWAw4Ny5c1i0aBFee+01DBkit18gIiIiIvOV+Y7a66+/DqPRiK5du+Ly5cu4//774eLigtdeew0vv/yyNY+RiIiI7EhlVH3eqco8UTMYDHjzzTcxatQoHD16FNnZ2WjcuDET+ImIiKo4fvVpO+XqowZcbanRuHFjaxxLpQpsGgiHEgnERiHh9apknbh5+l98U4wvqfFuufZricy6P6iPDzUGyIUH0vYAkJGvnrPWPdSGgTmvPSNuH/NftUhh5SR5RYoTcaFKLDRfTiwPLlITlcd+1kSJvdlKLkaI/d9J9fF1uqMHNJL3IXEWFuuN6hQujt2yUT2GLr+eUWJ6yc8N26jduw9uk5s9NxO6wSdskce27lhHiZ1Mz1Vih8/LHd6lpP+LTvJqA5eqqedLSs4HgCKhw3snncTy+TvPKjGn6moxgV6n/i4Pq4Ut81aqRTSAvIrB9gS5SKF2hFqUcSlXfX0tWYEg44y8ZN4+4dxKCfe6+82Tx+ZmqQtrZ6eoSf9eIXKRg7Q6g17SvlQck3nO/CUC6zdXP6vO6jyvaq7q6xjSQm6O6uyoXqMXzsrHtVta2cRDLmwree1reYVQS0+oqij3RI2IiIjuLLyjZjucqBEREZFFNE2zSn6ZOb3R7nRlrvokIiIioorFO2rXJO9PBpxvnA69XCHJky/6ivFFc4RcCme5saOkccoAJXYw4Euzt7eGhItqPomalXRVl1pqI8oOU9RmjS/HbBK3Tx39mhJb9vpQcWxippo7cvhPOe/jrmbqb2xS3sdHW+TGkmO7hSuxd1YcFsdmnMlQYj615Wavu5PUvK3zf8r5So3bq3ljBqEps/G8/BvuxWw1V0ivaa9ePppkR89eSsx31gIlFhoqn4OkfDWXzMdHzgVL1clzk+TnqLk+P/59QRwr5UFJv+XrNf1df0J9n1f3cxPHXhYaIju7yzlIZ06nKzE3X3W/Ut4bIOeuNWin5ioCwAWhcbBHoFwYlnFavcYvnkgTx0qNg6VY6mH5tZEa9Prf5S+Ozc9R8x2vXJLzHaWcOCnPrki4PgE5hznfKOeHqkcFVK8h/ztQR2j8u/+AnBdd8jOsMu5J8atP2+FEjYiIiCzClQlsh199EhEREdkp3lEjIiIii7Dhre1wokZEREQWYY6a7XCipuP+Wp5mjxWLBnQc6TLO7LHvbv9biS0p+lQc+42jumxXl8d9xLG/fpuuxH7/9T5x7J9H1cThPrsfEMeO8GymxJ76WU3wr+8qf+OuCb9Z7dt0vzj289/UhPfGb7UQxxq+P6HE7q2lJrevExqfAsBr59QPkjFCU1c9eVlSOjHQqr6aFC2XM8hNM09Eq883/ZdDZh+XHoPQQ7ZFVG1xbOCCxUrMw18tKjm6Xy6ScBAarXoICfN6+y3QaUjqF6EW+OQJzVf1jiFY2P6ATqPV755uq8RiZskFM+7+arK4VCAAyE1VpSR2SxreDrlbTsSft++iEksUigYAuRmwdA4BwFNIjk8+ohYOBLcIErd3EC5GD2dHcew5oXBArxhAKl5wdjev8AGQryW919HJRX0dpUbAAJBfpL6+7jXV6x4AskoUI2k67wOqGjhRIyIiIovwjprtcKJGREREFuFEzXZY9UlERERkp3hHjYiIiCzCqk/b4UTtmuo1qsNQIunz6/1yp+xLb6jd3D9/75zZj7Nzh5zcKnns4a1K7BuoMT37Z8hJ//h2lRJavkt+Dr8920mJjYjfJ44d+dl/ldj6NzorsfM58goC2oIFSuzrArmzuLSywKZzcoK/JnSU/13oJu8VJBeQdC/IEeOS0JbBSuzcn3KJwFGdrukSqWt6oJua4K+32sAJ4fW1ZOyBPfL1MaZPYyU2788UJaaXEC2tClAgJFQDcpd5B0f5S4EsYdUHF08XcazBQU1Yz7qsdpmvJiSFA8CO5FQlJq1AAMgrFhQVmN/9Xkrad9NZyUFaWaCBr9qRHwBOn1ULbvQKBPKz1eIYvUT6bOE18whQjysnVX6PdWgaqMRiOzYSx9497nsxbi7fcLWARHoNAMBNWE3iirAyAgDkCXHpmgPkgghvL/m6NSmIyLd9MQG/+rQdfvVJREREZKd4R42IiIgsolnpjpq0ri6Z4kSNiIiILGK89j9r7IdKx68+iYiIiOwU76hd4x3iBYcSXajP7pUTwI0fvq7Elrw3pkKOqddwNVm8+viB4li/OV8psZC4Y+LYjDlqArjDFTV5GgAa5akJ9vlF8q1qqaP95K2JSuyFf+4Sty+ccJcS+3N0f3HsvUu+VWJnMuVk3nvvUruxJ6RkK7Gzf6lJ4QBwwilAiQU2UWOAfN00aBcmjj1/Ru383iyqljjWW0hk35G8Q4llC4neAFCjnp8Sk4oGAKBmA/V8/fXiU+LY+p8sVGKRYeqqD/CSE953bj6lxKQkeEBOWNdL9pYSw/USuPVWLLiZXpf7AqFYRY+LkBjuU0Pt3g8AuVIxgfAm00vElwoqOoXKK31UczmgxC5fvCyOdRRWBtA7t0ahMMTRQd1er9Bj+xF1xQSPLnJhimeQet3oFURkJ6vvf+la8hCKlgAg5VS6EpMKYwDAVygguaRTbCKu1OEkr8RQ8vlquYVQn1HFYjGB7XCiRkRERBbhRM12+NUnERERkZ3iHTUiIiKyCO+o2Q4nakRERGSRqxM1a6xMwInarXCids3FE2kmKxPoif5puRJb/0Nncaz/fjVR+uLwl8SxS9xGKbG+nYOU2MovV4vbu/upCclfPdRCHNvhg/8pseo6Cc3wVJPmE4Su/gDgGawWHuwQkutfkB8JPpnpSuyVXRvEsX/vOKPEhv27pTh2ytZkJZYuJPIX5srdva8UqB9Gq//RShz7SL6a4H94u3qsetQr5qrOLdQVD46kpyuxAp2iEOm5SUUDgJxc//j334ljPYQE/+NCErteUreURK53LUoJ4HqFB+mJ6UpMKjAAAGehy3wND/W4snU+HzYkqsn8XiHyKhcGoRjg9H71+gTkBH3p3NSsqxaKAEDibrVYZMnfP4ljpddHr8gi8m51RYtk4TUH5NUcpGKE3Ax5VZGMM+oqJq6O8vUhrUAiba+nUFj9I0unUES6bvVWmJAKB/Tep1L8nE7BDN05OFEjIiIiixhhpa8+wTtqt8KJGhEREVmEOWq2w6pPIiIiIjvFO2pERERkEd5Rsx1O1K5x83GDwfXG6ZASUwHg7XvCldhOJ7l79cyH45XYktfVogEA6H/+FTWWr3YGX/LYXHH7aUIsMbqOONbdX+3sfXLEYHHst15jlVj+GLnTvpQkLCXY9vu1h7j98D1HlNg3h9TO5AAgvbdn75HHegjH5V2vhhJLPJEmbp8vJPh+/ZdcIHBB6KRuDRsTkpRY85rhSkyvw7uX8JpLyeZ6Hnqorhif8ot6zqT3jlt1tegAkIsB9Io6pM7vekno0ljdTvtC5/fEi+rzquYqf1zuFJLunUqsclKStFpAYCN5lYvL6WoSurTf7Etyl3t3fzXpfu5enWs8R13RQu9akgQGycUTSefUZH5LCj2c3NRzHuoaLo6VikIAedUGiVTo4VRdfh2lFSIuCc8LALxrqSt1SJ+VAOArnPM0nWu85PVYGVMdowboLFJj8X6odPzqk4iIiOxebGws2rZtC09PTwQEBKB37944fPhwqdssWLAABoPB5MfV1fQXOU3TMG7cOAQHB8PNzQ3R0dE4ckS9cVBZOFEjIiIii1z/6tMaP+bauHEjhg4diq1bt2L9+vUoKChAt27dkJNT+p1TLy8vnD9/vvjn1CnTRkjTpk3DJ598gjlz5mDbtm1wd3dHTEwMcnPlu5m2xq8+iYiIyCJFVvrq05J9rF271uTPCxYsQEBAAHbt2oX7779fdzuDwYCgILUvKXD1btqMGTPw1ltvoVevXgCAL7/8EoGBgVi9ejX69etn/gFWEE7UrqnmVg0OrjfyEfJz5IaEdb1rKbGwzQni2KMWPH71GUuU2HPd6yuxqS+rjw8AdWqr+RkbH/tZHHt61/tKbOWxtcJI4Km0qUps+FcLxbG5Qq6On9CM0ztePl9uQvPUZJ3mujXqqfs9uO20ODa4hfoGzTitNrzVa/AZITzW4m3mN7GV8mwAoOCKmouVeU5uHCpZKuTvSblGgH7DWUl1P/V1cBKarwJyQ9OaPur2xw7KTV2lvCI51wgICVDz7M5fkPPOpPPgo5NHJckSfsvXO676NdXj2hR/QhwrnVspFw0ALp1MV2K1W6nNZk//lSpuL92oeKCOfA6OCblkeg1cLwo5cXr5e6Ghan5WmvA+z8+Wr1t34dxO2r1SHCu9f9181FxFAPCp46PEzv+p5oFK5xsA3KT3U211nwDg7Ki+dzx0ct+y89VzrpfPVjIX1Fh0+zfFzcw0vQZdXFzg4lJ6nmRGxtXPcT8/uenzddnZ2ahTpw6MRiNatWqF9957D02aNAEAnDhxAklJSYiOji4e7+3tjfbt22PLli12MVHjV59ERERkEaNmvR8AqFWrFry9vYt/YmNjS398oxEjRozAvffei6ZNm+qOa9CgAebPn481a9bg66+/htFoRIcOHXDmzNVftpOSrk7QAwMDTbYLDAws/rvKxjtqREREZJEiTUORFVprXN/H6dOn4eXlVRy/1d20oUOHYv/+/di0aVOp46KiohAVFVX85w4dOqBRo0aYO3cuJk2aVI4jtx3eUSMiIqJK5eXlZfJT2kRt2LBh+OGHH7BhwwaEhcntovQ4OTnh7rvvxtGjV5OTrueuJSebpmckJyfr5rXZGidqREREZBFrf/VpDk3TMGzYMKxatQq//vorIiIiLD7uoqIiJCQkIDg4GAAQERGBoKAgxMXFFY/JzMzEtm3bTO7EVSZ+9XlNNZdqcNBJiC3pwpULSqxWpxid0b+Y/fi5GWoi7KELatLumk/lhPnct0KV2NC3W4tjM5Z+rcRSL8vFEwtqLFdiZ/eeF8d6BqnNSyXZKXIp9feD71FiD7wbJ4wEHmir/ha1UacYIFxIKP5TKCbwv8tf3P7UqXQlppdYHtQsUIld0WlIGhTipcROHJCT7n2EROXWUnK8TsL8su//UmJSQ1RATuB+f5ucq2EQigxS0tQEf72GppKkBPkcSI9VmGd+c9wCnYRr6fWxpNnrWZ3rTuIVqr7meo14pSKUzAvqe0d6vQCgSEhM/zJBLjyQGvFKxT2A3AQ2J1V+T0vHIL2ONXWeg5SIH+wu31+oIbxHLuu8NtI5l967uUKzawBIEYovwnQ+PzIy1WPIEM4LAAQFqJ+h+TplkVqJIgNDJRQTVEbV59ChQ7F48WKsWbMGnp6exTlk3t7ecHO7er0OGDAAoaGhxTluEydOxD333IPIyEikp6fj/fffx6lTp/D8888DuFoROmLECEyePBn169dHREQE3n77bYSEhKB3797lf4JWwIkaERER2b3Zs2cDADp37mwS/+KLL/DMM88AABITE+HgcGMyf+nSJQwePBhJSUnw9fVF69atsXnzZjRu3Lh4zOjRo5GTk4MXXngB6enp6NixI9auXas0xq0snKgRERGRRTQLv7YsbT/mj7314Pj4eJM/T58+HdOnTy91G4PBgIkTJ2LixInmH4wNcaJGREREFrF21SfpYzEBERERkZ3iHbVrkvcnA843TofU+R4AHluzW4nFvvCVODZnfxclNmGTnJTtckztMr8+UC0NNiQOEbcPMahJwn2+2SuO3ffvJ5RYfu9PxbHhkeYnVUvJxymH1OOSurMDcuGAT221szkgFz/oJfh7CJ29pU79UuJzafuVHP1bTVL2yDN/tQFpJQdATrBfKyRKf/2vZuL2a/eoSeyOTnLHc+k86HVHdxJWJsjNV4/L0VH+nbBQ6H4vJXXr7UOvUCM7OVuJ1YisIY6VuuJLxQh6j2VwUK9nvWvcWKgmfesl7UtJ917+atL9JSGxHZBXZ4iOkIs6Ngnvh4w0+fnmCcnxeqSkfXHFA6GwBgDSE9OV2ENPyMVbb2/4ToldOKJ+rgKAi6f6npYKSKTrGwC8w9TPpYs6BRU+NdSiHWed94O0uore+6HkudVy5aKaimQ0Xv2xxn6odJyoERERkUUqo+rzTsWvPomIiIjsFO+oERERkUUsbVZb2n6odJyoERERkUVY9Wk7nKhdE9YiGA5uNzpun9PpEH+PkJB8T/pQcWy7z9cqsUAhGRgAvBurCaPfhahJt4/u3CduX9gmQIkld2opjq3xyTIlVnCPnGTs66Em3V46mS6OlZKXRz2pJre/vyhB3L52qxAldkXYJwAcOa0eg4Negm6qmtAsJYZXF5J+9ca2bSIn+H72gLoyQNAWeSUHqUAg44ycGC4pEAoqlhxOE8dKxRNSF3QAOCOc25AA+bo9dlhdqcMzWD0H3jpJ2clCQYSURA8AOcJYS1YQkM4XICfzS8eg91hSV36pGAEA3KWu/jrHVSgkiEvvB2kcAHgEqq/vkp//Fsdqwm0NvSIaaXWFAp0O/hK94gmJtKLF4bRj4thqQnGMq7f8mhkM6usrvUfydD5/XIRzk6zzuSh9XvrpFHW4Cauo6L2+Jc+5prNCB1UNnKgRERGRRfjVp+1wokZEREQWMcI6FZvsznFrrPokIiIislO8o0ZEREQWMWoajFYoBLDGPqo6TtSuybp4GQbXG6ej94OR4rixbesrsS8P7RfHTuxWR4kNnb1HHOsZpCb+xjw1UIktjXxV3L7fD52VWGH3x8SxaU3aK7EZh34Sx763Qe2UrSc9MUPd77eHzN7+wslLSsxJSL4G5MTwyzqd1H3DfZSYlDwtFUMAgFeQmhyfcEZ9rgCw81CKEsvNyBXHSpzd5ecrJWC3vMtfie1NUjvyA3Kn/uM6nfar+6lFFecvqAUZgJw0Lz1WdVf5o0Z6faXXBpCTvfUKD6Tu98Yi+UuWoivqWOmxLHkdpe0BwK2amvCekSu/DgF1fJRYutDp31ko+AGAmkJRx4Mtg8Wxvx5Qr1txBQEAWefVlTb0jkF6LaWVDXLT5XMbWl8t3nrplyPi2CvC6yOtBAHInx/S8/XSWTHB2VG97vyFYwXkc6B3bqUVQPSu8ZKrIxivFEBdA6ZiseGt7fCrTyIiIiI7xTtqREREZBFWfdoOJ2pERERkEX71aTucqF1jcDCY5AL0iJAbfNb3aazEPvjxV3HswdH/VGITGp0Rx0oNI11+/k4cKwk+dk6JjdizShz7/VE1v+qPjh3EsefbqbkU7x+5KI71ClFzYqSmmVKDUEBupCk1hQXk5rhFtX3EsRnn1CayNRvWNPu4CoRmknp5I8El8kauO6uTJ1Ozvppjdnav3BxXOo9//HFKiW0Y3UXcvqfQxFbv+aZlqLmC0vkGgDzh3Ei5XJd1mnbqnUeJlA8XrNNY9piQb6jXsFbKIZJieo1aW4Sp1+2mHWfFsaeFpr16OXnwUx9Pug6knDEAyBBywX7Xaa4r5e9Z0iBYLyfPyU3OubyZ3nVwScg71cvvqiY0VXavKX+OXxZy/aTrS8oZA4ALZ9XPFL3GtFKeXbbOWKO7+c0qSubUajr7o6qBEzUiIiKyiNGowWiF7y2tsY+qjsUERERERHaKd9SIiIjIIsxRsx1O1IiIiMgirPq0HU7UrnFwcoCD043E0de+Py6O83hcLRzQS1KuM3qBEqtRz08cO7F7uBLzWX1UifWPu0/cPmW52nT3A50E07QTarL4/QY5mXfnHrVIQU/mOTWp2dFJ/Xa9qEBOmH2sU4QS+05ongoAWWlqMrDe61C9htrANU9I6tZLaJYSjxs3UIsRAODkBTVBP6NjI3Fs5Cnzz22Q0Pw0S0j2fnfbCXF7qQmtb7ivOLZWoNp82U14HQHgqJC0r9ekWCIlYOttL409LjRJBuQEfel11BsrXQt618ceoVhE0+m2Xk1o/KuXhH4lX02ar+akJrd7Co1tAbnJsJQED8hJ83oNgrNT1GupUbMgcewpoZBHer5656CZsN+WQnNwAFi9Xy08SjueJo6Vrn2pCCbrslyoIRU+6RXnJB5UmwnrkQoiAiPk92lqietZE4p6qOqwuxy1WbNmITw8HK6urmjfvj22b9+uO/bAgQN44oknEB4eDoPBgBkzZtjuQImIiO5QRu3G15/l+eEdtVuzq4nasmXLMHLkSIwfPx67d+9GixYtEBMTg5QU+TeSy5cvo27dupgyZQqCguTf6IiIiMi6rq/1aY0fKp1dTdQ++ugjDB48GIMGDULjxo0xZ84cVK9eHfPnzxfHt23bFu+//z769esHFxf5ay8iIiKi25Xd5Kjl5+dj165dGDt2bHHMwcEB0dHR2LJli9UeJy8vD3l5N/KTMjPlnA0iIiKSserTduxmonbhwgUUFRUhMDDQJB4YGIi//vrLao8TGxuLCRMmKPF6QZ6oViKJ+fgFOfF4Z7KahF5bJ5lXStrX60J+PkfoDC6sVvCfS3JX7s+EmJS4DADzXm6lxEb9ICeh//5KVyXWbsJP4ljpDvb/RnVSYk98vVvcfu2+JCUmdQsHgCuX1I7leudW6uZuFBLApRgA1L9LXUHg6Bl1dQdAvhZyOsmrBZwYPk2MS3KExPIiIZYtxADAu5a6YsLFY3KitUQvkT5DOA8BQqHFhWPyahZS8rRU6AEAXkHqudW7xqVrQS/ZWypCcReuO28XuUv9SeF9rnfdSo/l4Ch/sXHxqHrOfITVN6TrAADOCoUWesclrUIgPRYgv/ekogG9/UrXko9QLAMAqZfVYhU90uoIUiGR3liJXkGFo/Ca6RVESKsjBATIBRHnhfdT6mn5s6bk55rm6AD56q44RZqGIit8bWmNfVR1dvXVpy2MHTsWGRkZxT+nT5+u7EMiIiIiEtnNHTV/f384OjoiOdm0xDo5OdmqhQIuLi7MZyMiIiqHIuPVH2vsh0pnN3fUnJ2d0bp1a8TFxRXHjEYj4uLiEBUVVYlHRkRERCVd/+rTGj9UOru5owYAI0eOxMCBA9GmTRu0a9cOM2bMQE5ODgYNGgQAGDBgAEJDQxEbGwvgagHCwYMHi//77Nmz2Lt3Lzw8PBAZGVlpz4OIiIjIGuxqota3b1+kpqZi3LhxSEpKQsuWLbF27driAoPExEQ4ONy4CXju3DncfffdxX/+4IMP8MEHH6BTp06Ij4+36LEv5RbCsUR3fr3E8lV/qwnYaTqFBxKpwAAApgsJurkZalJ1Ye8+4vbVfn9XiaUcShXHviYUKVw6mS6O7TLnNyVW6+4QcewFIXm5c6L6WOmJcnJsl671lNjmnWfEsd5hanK8lOQMyEUZUoJvXqacxH4iMV2J6SVlH0pQCyLaFi4Wx1b3c1NihTodxrPOqx3SpU77QQ3UwgcAOCskVWfqdKn3F8aeE84BAHgKCf65QjFA0xbB4vZJ2WqyuLQ9AFwROscXFciJ9FJBgleI2k0ekLvypwlJ3Vd81dcLkAsE9D4/pAKB4EYB4lhphYZ84XzpFV9ENAlUYnrFJtI51yu+yEqSVrnwEcdKxR7S+dJ770rRpcJ7AQCa1K+hxLbprAogFRi5Ca+vj4/8Pr8grPShV3AjFbbovQ6WFEQ4l1ilwnilAPK/LBXHaNRQZIVutUZ2vL0lu5qoAcCwYcMwbNgw8e9unnyFh4frLtVCREREFaMIGhysUfUJ/ht+K3aTo0ZEREREpuzujhoRERHZtyIj4MCqT5vgHTUiIiKySGVUfcbGxqJt27bw9PREQEAAevfujcOHD5e6zeeff4777rsPvr6+8PX1RXR0NLZv324y5plnnoHBYDD56d69e5nOS0XgHbVrMq8UmMxa9RJppWTPxjpdtfcICbo+QhI8AKQJifgBjdQO76HTZ4rbS4nSegm6Ugdt6bEAIF1IIs9IURNpASCknp8S2xmpJpv7C0m/AHBPiJrgnyAkqwNysnZAqJwsLiX+Zgjdvj11Vpjwq64m8zo76PyOI3Rzv6KTWC4lCefnyJ3YM8+pCdTSedx0Kl3cvmTicWmPDwD5wq+40qoAAFAgFD+4uqlJ8KlCh3oA8BZWJshMkpPFpaR/S1YAcBeS8wG583uuULiglyweIrzml3QS/KXCgaw0uRjJSTiPUuGAVBgDAM6O6vHqLYAtFdzoCWyiPodLwucXANSsrxa35AjPV0ruB+TP2y511c8ZAPjl7wtKTFqRA5CLUKRVCNLT1esAAAKF90OacM0AQGSQugpBgk6hl1QgpHdurpQoSDDmmv/63c42btyIoUOHom3btigsLMQbb7yBbt264eDBg3B3l98H8fHx6N+/Pzp06ABXV1dMnToV3bp1w4EDBxAaGlo8rnv37vjiiy+K/2xP/VY5USMiIiKLFBk1OFihYtOSytG1a9ea/HnBggUICAjArl27cP/994vbLFq0yOTP//3vf7Fy5UrExcVhwIABxXEXFxerNte3Jn71SURERBax9lefmZmZJj95efJd6ZIyMq7eDffzk++ySi5fvoyCggJlm/j4eAQEBKBBgwYYMmQILl6U1yeuDJyoERERUaWqVasWvL29i3+uN7bXYzQaMWLECNx7771o2rSp2Y8zZswYhISEIDo6ujjWvXt3fPnll4iLi8PUqVOxceNG9OjRA0VFcr87W+NXn9cU5hXCoUTDW/9wX3GclE/yp5BXAAB1hRyi8zrNcR/rFKHEfv7zvBLTa0zr6q1+n14jQv4tQ8qHk3IjAMBPyAfRy9U5uuOsEtvTVs1nuXBE/k1lvtAcM/WwmncCADWFxq4pOg1cqwl5UFIjTr3GoRKpiaWepMNyPsryl9oqsX+vPSaOlfKVpOcgNUQFgP/rUluJzdDJS3KrpuaC1ayuxgBg+171Gg1tqTa3zdLJa0wRcvKkJroAEBGg5vocOZ0ujg0OVPehl7QsNZaNEPItzwqNXgE5H03KcQOAbCFf0sVLzoXRa5przj4BuUmyq04D1yKhAauU56dH7zWTGum6+6m5kSk67xGPQPU1lz4XAcBHyLk8q9OoWWqYLeVANtDJ/5O+rju655w49oBwDnSb2Ar5aHqfNSXf/3q5hxXJaKW1Po3X9nH69Gl4ed3IM75VjtjQoUOxf/9+bNq0yezHmjJlCpYuXYr4+Hi4ut54L/Tr16/4v5s1a4bmzZujXr16iI+PR9euXc3ef0XhRI2IiIgsUqQBBms0vL22Cy8vL5OJWmmGDRuGH374Ab/99hvCwsLM2uaDDz7AlClT8Msvv6B58+aljq1bty78/f1x9OhRTtSIiIiIzKFpGl5++WWsWrUK8fHxiIhQv4mSTJs2De+++y7WrVuHNm3a3HL8mTNncPHiRQQHy0vf2RonakRERGSRIk2z0h018/cxdOhQLF68GGvWrIGnpyeSkq6urezt7Q03t6trtQ4YMAChoaHFOW5Tp07FuHHjsHjxYoSHhxdv4+HhAQ8PD2RnZ2PChAl44oknEBQUhGPHjmH06NGIjIxETExMuZ+fNbCYgIiIiCxSdG1Rdmv8mGv27NnIyMhA586dERwcXPyzbNmy4jGJiYk4f/68yTb5+fn4xz/+YbLNBx98AABwdHTEvn378Oijj+Kuu+7Cc889h9atW+P333+3m15qvKN2TeGVQhhKXC/JOk03pWTPVo3VhHkA+POomjQvJYUDwF6dROWbSUn0gJwMfEUnofmK0MTRO0zODUg7nmbWYwFAULNAJTZ1W7IS86ktN6HUK2iQFAqNVvWKHKTmljWE5rZnDqaI27v5uikxvWRxR6Gx7L9i6otjHwntosSeSt0n71dIdPZ1VY/rkk5j2bxC9cPQVydZ3NtVfawjQsNdPecTkpSYj9AUFpAbmuol0W///aQSqyEk/QNAhnB9SIntgHw9J0vvET/1fANAmpDMr/ccpAIQvebaUrNYqTGtXkNUZ+GzplB4L+hx9pD36yE8hws65zYv07wCHakRMABcEYpN3HSeb6bwmukl7UsFGNJrs1Wnka/UYDzy7hBxbIbwmtX2ka+lXVsTlZhU7AIA7v43Ch3ulIa3mhl33+Lj403+fPLkyVLHu7m5Yd26deU4qorHiRoRERFZ5GoxgXX2Q6XjRI2IiIgsUmTUYLDxygR3KuaoEREREdkp3lEjIiIiixhLLP9U3v1Q6ThRuyYszAuOJZJvk3QSVqWkbkeDnMSenpihxFw85f2a2+ler1N/QKOaSizlkNztW+LqLXcs9xM6g0fqJFWvX6921ZeKH6TkfEBOPPaLkFeIqC0VA+gkZUvn9pIwVq8Y4fyfanJ8dZ1zID23NbvljuUPpC9WYlk6RSVSAYaHULiQISTnA8CZbDWJXO+6zRaS66vrFB5Ir6+UnK93bt291WTvAqEQAJBX39Dbr5Q0rzfWU1jxwM1JPY9ndVbUEItVItVVSQCgMFd9bnrv/TwhkV4qHJCS4AEgQliF4NBp9TMJAAzCtVCgU5iSIby+emPFYhGhnX2BTov7zHPqaiO5Op/N0ioGrjrvB6lEQHrvZuicL+l5pQuvFwBcuXRFjekUakiFAyWLBvTGGuVLu0IVGTWAX33aBL/6JCIiIrJTvKNGREREFikCAGtUfZZ/F1UeJ2pERERkEX71aTv86pOIiIjITvGO2jUXsvPhUKLznm736wtqEvqfOom0kkCh2zgAXBKSZqUkY3d/udO2VDjgGaQm1wJy0myeTmdxKQF7p05StZRgL23vLhRkAECmcAzSCgQAcEZI5tXr4C0lt0sJzXrd5KXnJSUT6+23uk4X8uea+SixXfvlxOFqLupbde9moYu5m/yWTgpXizJOHZNfR+k86q3EIBWhZJ5Vr2XdAhLhNdcrbJH2ofeaOzmqr0+RUHyhJ+2CukqGdy15RQ3pGpceHwCchM+V9MR0caxUWOIVohbRZOmsouIndM/Xu27N7dQPAC5CYYmnUNwDyNeN9PrqnS/p89JN5zmkCY91ReezRlohRlohIlCnmElq0pqu8zpInyspOis2SCt46F0fwSUKVqTPnYpWpGmAjdf6vFNxokZEREQW4UTNdvjVJxEREZGd4h01IiIisojRCMAK37gabf+t7W2HEzUiIiKySJGmQePKBDbBido1uem5MJToGn7xoppMDMiJsFJyLSB3bc9KM3+/UpKwl5AgDAA5QvKz1BEbkJOfpWR1QO6kLnUxBwCvUPXYpI7lWTrFF9J51Du30nNz0SkAKRSKMqTn0LR1qLh9stBxXC/5OU8ofriik4j/8S41mV8vOf6CUMDh4Kg+B71E/HAf9Ty2bxEsjt0vFLZIq0YA8usjJazrPS93P7U45oJOkUP1GupYKQkekFcQsaR7vtTl3pL3k/yKy0ns0mPpcRQKIvRWXNh6Uu2/r7cKgrPQKV/vWpKS26UVEwAgREiOzxcS31NOqfsE5AISqWgAALyFz8ZMnQR/cYUH4TMwS+e6F69x4bUF5M9xvXObL3zW6H3mn/v7xio1mk7RFVUNnKgRERGRRYqMmtlLH5bGyD5qt8SJGhEREVmEX33aDqs+iYiIiOwU76gRERGRRVj1aTucqF3j6uMKhxLJoFI3ewDwClI7cOfqdPWXOOgkoUtJ0Z7CY+l1qZb4Ct3oATkRVioaAOQE/WxhdQZA7sAtJcfqdUeXutTrJaFLhQv5V+RkcanjuIuXmgSfpPM6egtJwoe3nxHHBjULVGJ6z7e2cAxndYonpP3mZwtFDjrnK6dAfW1aB8mrXEh2C68jIHeel647vfdThlC4oJeYLu1DL4G7qEAdq7c6gnTOpHOrp46Q7H1WpxjJV3h9jwtJ/4CccC4VNNSI8BO3lz6X9FYbkK5RvdVKpAISvdcsXbhupKKOsLryc5AKD/SKJyS615KZ14f02QEAPsJnc6bOe0R6HfXO7V0lVhu47pROwUzJ49VyC2H+FWsdmpVy1Kyxj6qOX30SERER2SneUSMiIiKL8I6a7XCiRkRERBbRNCtN1Fj1eUucqF1z+cJlGErkb+jlNkj5WXr5LJ7Bah6DXr6SRzW16WVEgBo7rJMHkZ+j5n1I+WGAnCOi94aT8nf0zo2Uoybls3gIzTUBwE3Yb65O3pl0zo1CPgsg56NJzS318kbOnFcbVgY0qimOFfPhdPLOtp9T9xuq0whz16ZTYvxmzu5yztZeYb9BOq9DYqaad6bXLFYi5RDp5RUVCo069Rp8Sq+PtD0AhNXyUWJ/7ZTzCoObBSmxi8fSlFhoS7lBsJSPJjXcBYBM4Xi9w7zFsdI5k3LyCnTOgfSe1stFlT6X9K7bzLNqXqHUjBgA3ITzkCkcg5SLBgChwjEk6VxLaULTb73PBOn9n7w/WYn5CA17AbmxtV5TaCkvUO/6OCGcW73nUPJz2Cg0v6aqgxM1IiIisohmpT5qvKN2a5yoERERkUWYo2Y7rPokIiIislO8o0ZEREQW4R012+FE7Rondyc4uN5I1M1OkZsMSom/UmIqABQIifAGg5z0GSQUDqTlmp/ALdFLBpaOV69RqiVNVaWEZFchdkFImAXk45UaUwL6jYMl0geBVPigR3od3fXOl1DAofdYUoPeczr5Gk5u6mtmbvEGAJw8k6HEknUawPoLz02vWayUKC1dM846hQvVfdT9ZiapRRZ6j6WXwH36lNpE1iNQfY8BQKFwjbl4qsebp1OcIzWFvqTTmFrvGCRSc2upeaol9BLT9YqcJFLhgKPO+zH1tHrdSddomk5T14w0tcGvXgGJVGhhzJOfb0aqelzGIvW9p1cEIzUod6/pLo4V36dCgRMgX896xVv+XjeuhSInR1wQR1UgK03UwInaLfGrTyIiIiI7xTtqREREZBHNCKvcDdO41uctcaJGREREFtGMmpUmavzq81b41ScRERGRneIdtWuK8opgLJHo7xmkrioAyJ299ZLrpURUvQ7vycKKB1KCr5TECgBSjcLFoxfFsdJvMHV0uq67+anJ3ud19it1lD/9V6oS0+tiLiWL6yXzSqsYnN5zThwrJbJLicd6CdVSAneS0LkeAFx91LE5wmsLAPUaByqxi9lycrzUybzginot6v12WitUfW3OJsnXUppwMel1Und2UuMe/urre0lICgeAXCGRX+/6kFYm0CtSkF4zvWspN0NdiUHv/S+5eEK9FvSKOvSOQSKdB0uKCaTr2UGnmKlIKDK4LKy4oHcMV4RzCMhFKJZ06pcS8Y058ndljWqphV6HhVVFAPn9L702GUIRDiCfgzo6hSJ/CZ+BVy7J7wdpNRu993Ta5RvFLUadFVwqEu+o2Q4nakRERGQRTtRsh199EhERkd2LjY1F27Zt4enpiYCAAPTu3RuHDx++5XbLly9Hw4YN4erqimbNmuGnn34y+XtN0zBu3DgEBwfDzc0N0dHROHLkSEU9DYtxokZEREQWud7w1ho/5tq4cSOGDh2KrVu3Yv369SgoKEC3bt2QkyOnlwDA5s2b0b9/fzz33HPYs2cPevfujd69e2P//v3FY6ZNm4ZPPvkEc+bMwbZt2+Du7o6YmBjk5spf6dsav/okIiIii2jQAGssyo6r+8jMNG2E7uLiAhcX01zPtWvXmvx5wYIFCAgIwK5du3D//feL+//444/RvXt3jBo1CgAwadIkrF+/HjNnzsScOXOgaRpmzJiBt956C7169QIAfPnllwgMDMTq1avRr1+/cj/H8uJE7ZqigiKTZFIpcRmQv0/XS/CVkoH1komlx2vawF+JHdJJGk1PVJNeiwrkpNtQoXAgR6fIwUlYxUCvS700tjBPTRbXO7dSgq+UeAwAWWlqorNfXT9xrNTJPDRUTTzON8rnKz1d/a1KOla9x5KKBgDgQqa6X73rQ29Fi5tlp8i/WaYJhR6zetcVx47432klpldokbhbLeDwDlMfy1tYeQMArgjd/vV+w5aucY8AuRu8o596vNJKEID8/pWKhvRWmHAUCiqkAgW9x5JWvgD0O9LfTO+aCRS2T9RJrpeKMvTe59Lj+QkFJACQLZxH6dzqnS9pJQe955sgFDnpvWbSufUUVgtwaVBT3F66lk7pFHpJhRJ6K65Ix6t3fTgZb3wGGXVWa7id1KpVy+TP48ePxzvvvFPqNhkZVz8T/Pzkz34A2LJlC0aOHGkSi4mJwerVqwEAJ06cQFJSEqKjo4v/3tvbG+3bt8eWLVs4USMiIqLbj7WLCU6fPg0vrxu/5N18N+1mRqMRI0aMwL333oumTZvqjktKSkJgoOkvy4GBgUhKSir+++sxvTGVjRM1IiIisoi1J2peXl4mE7VbGTp0KPbv349NmzaV+xjsHYsJiIiI6LYxbNgw/PDDD9iwYQPCwsJKHRsUFITk5GSTWHJyMoKCgor//npMb0xl40SNiIiILFIZVZ+apmHYsGFYtWoVfv31V0RERNxym6ioKMTFxZnE1q9fj6ioKABAREQEgoKCTMZkZmZi27ZtxWMqG7/6vMbJzQmGEonr+UKSMwBUkxLmheRYACjKVxNGLUlu9RYeS0qo1uMb7mP22MxzmWI87C61oCFT5/nmCAn+Qc3URHq91Rn0EmwlUnK93vb52eprmZSiJv7qdUeXOrRLSc6AnAgvFQ0A8jXm5S8nx7vXVONSTC8p++0O6m+Gr22QV3KQkrUzz8rXh1+ErxKTzmOOznFJr5neB7f0WFLxBgCc3XteibkJq0YAciK9dAxZOon4PnV8lJj02gDyZ4IeKYlcev/71FYLYwDgqJDcrrfqQ1JCshJzcpP/eZA+AyGsCgDI7z1LViZwFYpY0nVe89rCMQgLLgAAMoR9pOkUA0ikz3G951BDWG1Ar3grPTFdiYU2lAsackscg9H8BS+spjIa3g4dOhSLFy/GmjVr4OnpWZxD5u3tDTe3q8UvAwYMQGhoKGJjYwEAw4cPR6dOnfDhhx+iZ8+eWLp0KXbu3InPPvsMwNV/S0aMGIHJkyejfv36iIiIwNtvv42QkBD07t273M/PGjhRIyIiIrs3e/ZsAEDnzp1N4l988QWeeeYZAEBiYiIcHG5M8Dt06IDFixfjrbfewhtvvIH69etj9erVJgUIo0ePRk5ODl544QWkp6ejY8eOWLt2LVxdzV+yrSJxokZEREQWqYw7apoZfdvi4+OVWJ8+fdCnTx/dbQwGAyZOnIiJEyeafSy2xIkaERERWYRrfdoOJ2rXVHOrBgfXGw0E9RqaOlWX4xIpB0nK2dDb7wmh0aoeqfGnXj5M2slLSkxq2gkAmcLx6u1XyrOTmtvq5elJb1gxHwaAr5/ajDNLJ+9D2of02ujlmEj5aJeEcwgAnkFqPoqU4wbo5zFJ0o6nKTFjkXq+glvIVUoOQtlQR528ou//OKXELqddEcdK+UZSbpXec81JVBv06n1w52Wpr5l//RriWKnprl7+noun2q9Jum718hKlzwq9vFWpMewFnZyrnFT13LgL2+s1xpXOo6/wXAEgw1PIkQ2Trw8pVy/lYIo41qe2jxKTzk1eptwEO0V4T+vl2Z04pr5HpNcWAFyFuPS5VlPnPZIlHG+2kPcKAGnC66DXtFe6ljx0PpculngdNJ3rjaoGTtSIiIjIIryjZjucqBEREZFFNM1Ka31aYR9VHfuoEREREdkp3lEjIiIii/CrT9vhRO0aY6ERKJHkrpdYrpfcLpGaeXoKzQ8BOUE3VEh4TRWafgKWNZF0EJrFZl9QE5cBIOVQqhLTa7ApPV+pcEAv+Vmi9xykIgcpARyQE4qlhGS9ZHMp8dfNVy1mAOSEYo8A85vjZuq8DlKxiZRcr1eo8ca6RCXWRCdRWjo3esUEUmK4dL71kuulsXqFLV4haoGAXmGLlIhfq6nafBkAHIXXN82C5GzpGtV7HdIuqIUleted9FkjFaZI731Avm5ThfMCyNezXhNs6Xpu1kwuYjklNMF2EJrYSkUWAJAiNFrWe831igwkRuHrNqlYJF2nEEh67wZHyoUtF4XPdukcAICPUMCRsOW0OLZkYYlmQbNwa9E0K03U+NXnLdnlV5+zZs1CeHg4XF1d0b59e2zfvr3U8cuXL0fDhg3h6uqKZs2a4aeffrLRkRIRERFVHLubqC1btgwjR47E+PHjsXv3brRo0QIxMTFISZHLvzdv3oz+/fvjueeew549e9C7d2/07t0b+/fvt/GRExER3RkqY63PO5XdTdQ++ugjDB48GIMGDULjxo0xZ84cVK9eHfPnzxfHf/zxx+jevTtGjRqFRo0aYdKkSWjVqhVmzpxp4yMnIiK6Q1hrksaJ2i3ZVY5afn4+du3ahbFjxxbHHBwcEB0djS1btojbbNmyBSNHjjSJxcTEYPXq1eL4vLw85OXdyGXKyLi6yLGWW4iSWSV6DQSNjuavfqsVqHkqRp1Gh5rQ9LJQaPaoe1wQmirqrUgs5KjpNkzMV+OWNFfUhFwdS86h3nOQ8hp0z42T8PuIoxrTfV7Ca6bp5MlIr6Mlr5neWGm/0mtjFJrNAoBRyGGRri8AMOYKceGx9I5LE3LMjNV0rnvh+WpCI18AMBrVa0HL17k+hOPSOzdSLpd4XDp5QNJ+xXMIQCsUXnOdhrfi+9SS96P0vITrHgA04X2md1zScyvSu5akcy7kZxn13ufS66Dz77r0ftIjfa5Id3Z034/CWL3rS3wOOpMTcR9mvPeu/7dN8710PgMrbT9VmF1N1C5cuICioiIEBpom/QYGBuKvv/4St0lKShLHJyUlieNjY2MxYcIEJX5p0oYyHnXF+a2yD0BHRmUfwG1GXsOgYqilH/r+sMLjSanWcvp15VPXW7AOOeXedmz9+FLJjromwJ3HGp+L6RaMld5nFy9ehLe3XCRkLc7OzggKCkLS13utts+goCA4O5tfZHansauJmi2MHTvW5A5ceno66tSpg8TExAq/wG9XmZmZqFWrFk6fPg0vL7Xy7k7H81M6np9b4zkqHc9P6TIyMlC7dm34+flV+GO5urrixIkTyM+Xl0MsC2dnZ7i6ulptf1WNXU3U/P394ejoiOTkZJN4cnIygoLk8u+goCCLxru4uMDFRW0J4O3tzQ+AW/Dy8uI5KgXPT+l4fm6N56h0PD+lc5AW9a0Arq6unFjZkF0VEzg7O6N169aIi4srjhmNRsTFxSEqKkrcJioqymQ8AKxfv153PBEREdHtwq7uqAHAyJEjMXDgQLRp0wbt2rXDjBkzkJOTg0GDBgEABgwYgNDQUMTGxgIAhg8fjk6dOuHDDz9Ez549sXTpUuzcuROfffZZZT4NIiIionKzu4la3759kZqainHjxiEpKQktW7bE2rVriwsGEhMTTW7vdujQAYsXL8Zbb72FN954A/Xr18fq1avRtGlTsx7PxcUF48ePF78Opat4jkrH81M6np9b4zkqHc9P6Xh+qjaDxvUbiIiIiOySXeWoEREREdENnKgRERER2SlO1IiIiIjsFCdqRERERHaqSk/UwsPDYTAYlJ+hQ4fqbrN8+XI0bNgQrq6uaNasGX766ScbHrHtWXqOFixYoIytyo0Pi4qK8PbbbyMiIgJubm6oV68eJk2adMs19eLj49GqVSu4uLggMjISCxYssM0B21hZzk98fLx4zekt+3a7y8rKwogRI1CnTh24ubmhQ4cO2LFjR6nb3CnXz3WWnqOqfA399ttveOSRRxASEgKDwaCsW61pGsaNG4fg4GC4ubkhOjoaR44cueV+Z82ahfDwcLi6uqJ9+/bYvn17BT0DsjqtCktJSdHOnz9f/LN+/XoNgLZhwwZx/B9//KE5Ojpq06ZN0w4ePKi99dZbmpOTk5aQkGDbA7chS8/RF198oXl5eZlsk5SUZNuDtqF3331Xq1GjhvbDDz9oJ06c0JYvX655eHhoH3/8se42x48f16pXr66NHDlSO3jwoPbpp59qjo6O2tq1a2145LZRlvOzYcMGDYB2+PBhk+uoqKjIhkduO//85z+1xo0baxs3btSOHDmijR8/XvPy8tLOnDkjjr+Trp/rLD1HVfka+umnn7Q333xT+/bbbzUA2qpVq0z+fsqUKZq3t7e2evVq7c8//9QeffRRLSIiQrty5YruPpcuXao5Oztr8+fP1w4cOKANHjxY8/Hx0ZKTkyv42ZA1VOmJ2s2GDx+u1atXTzMajeLf//Of/9R69uxpEmvfvr3273//2xaHZxdudY6++OILzdvb27YHVYl69uypPfvssyaxxx9/XHvyySd1txk9erTWpEkTk1jfvn21mJiYCjnGylSW83P9H9lLly5V8NFVvsuXL2uOjo7aDz/8YBJv1aqV9uabb4rb3EnXj6aV7RzdKdfQzRM1o9GoBQUFae+//35xLD09XXNxcdGWLFmiu5927dppQ4cOLf5zUVGRFhISosXGxlbIcZN1VemvPkvKz8/H119/jWeffRYGg0Ecs2XLFkRHR5vEYmJisGXLFlscYqUz5xwBQHZ2NurUqYNatWqhV69eOHDggA2P0rY6dOiAuLg4/P333wCAP//8E5s2bUKPHj10t7mTrqOynJ/rWrZsieDgYDz44IP4448/KvpQK0VhYSGKioqU9AA3Nzds2rRJ3OZOun6Asp2j6+6Ea6ikEydOICkpyeT68Pb2Rvv27XWvj/z8fOzatctkGwcHB0RHR1fZa6qqsbuVCSrK6tWrkZ6ejmeeeUZ3TFJSUvEKCNcFBgZWibwHc5hzjho0aID58+ejefPmyMjIwAcffIAOHTrgwIEDCAsLs93B2sjrr7+OzMxMNGzYEI6OjigqKsK7776LJ598UncbvesoMzMTV65cgZubW0Ufts2U5fwEBwdjzpw5aNOmDfLy8vDf//4XnTt3xrZt29CqVSsbHn3F8/T0RFRUFCZNmoRGjRohMDAQS5YswZYtWxAZGSlucyddP0DZztGddA2VdP3fIkv+nbpw4QKKiorEbf7666+KOVCyqjtmojZv3jz06NEDISEhlX0odsuccxQVFWWy4H2HDh3QqFEjzJ07F5MmTbLFYdrUN998g0WLFmHx4sVo0qQJ9u7dixEjRiAkJAQDBw6s7MOrdGU5Pw0aNECDBg2K/9yhQwccO3YM06dPx1dffWWrQ7eZr776Cs8++yxCQ0Ph6OiIVq1aoX///ti1a1dlH5rdsPQc3WnXEN3Z7oiJ2qlTp/DLL7/g22+/LXVcUFAQkpOTTWLJyckICgqqyMOzC+aeo5s5OTnh7rvvxtGjRyvoyCrXqFGj8Prrr6Nfv34AgGbNmuHUqVOIjY3VnYjoXUdeXl5V7m5IWc6PpF27drf8mut2Va9ePWzcuBE5OTnIzMxEcHAw+vbti7p164rj76Tr5zpLz5GkKl9D113/tyg5ORnBwcHF8eTkZLRs2VLcxt/fH46Ojnfsv21VwR2Ro/bFF18gICAAPXv2LHVcVFQU4uLiTGLr1683uYNUVZl7jm5WVFSEhIQEkw+NquTy5ctwcDB9mzg6OsJoNOpucyddR2U5P5K9e/dW2WvoOnd3dwQHB+PSpUtYt24devXqJY67k66fm5l7jiR3wjUUERGBoKAgk+sjMzMT27Zt070+nJ2d0bp1a5NtjEYj4uLi7ohrqkqo7GqGilZUVKTVrl1bGzNmjPJ3Tz/9tPb6668X//mPP/7QqlWrpn3wwQfaoUOHtPHjx1f59hyaZtk5mjBhgrZu3Trt2LFj2q5du7R+/fpprq6u2oEDB2x5yDYzcOBALTQ0tLj9xLfffqv5+/tro0ePLh7z+uuva08//XTxn6+3Vxg1apR26NAhbdasWVW2vUJZzs/06dO11atXa0eOHNESEhK04cOHaw4ODtovv/xSGU+hwq1du1b7+eeftePHj2v/+9//tBYtWmjt27fX8vPzNU27s6+f6yw9R1X5GsrKytL27Nmj7dmzRwOgffTRR9qePXu0U6dOaZp2tT2Hj4+PtmbNGm3fvn1ar169lPYcXbp00T799NPiPy9dulRzcXHRFixYoB08eFB74YUXNB8fnyrdWqkqqfITtXXr1hX327lZp06dtIEDB5rEvvnmG+2uu+7SnJ2dtSZNmmg//vijjY608lhyjkaMGKHVrl1bc3Z21gIDA7WHHnpI2717tw2P1rYyMzO14cOHa7Vr19ZcXV21unXram+++aaWl5dXPGbgwIFap06dTLbbsGGD1rJlS83Z2VmrW7eu9sUXX9j2wG2kLOdn6tSpWr169TRXV1fNz89P69y5s/brr79WwtHbxrJly7S6detqzs7OWlBQkDZ06FAtPT29+O/v5OvnOkvPUVW+hq63Hrn55/rnsNFo1N5++20tMDBQc3Fx0bp27ap8dtepU0cbP368SezTTz8t/uxu166dtnXrVhs9Iyovg6bdosU6EREREVWKOyJHjYiIiOh2xIkaERERkZ3iRI2IiIjITnGiRkRERGSnOFEjIiIislOcqBERERHZKU7UiIiIiOwUJ2pEREREdooTNSIiIiI7xYkaERERkZ3iRI3oDtG5c2eMGDHC5o/7zDPPoHfv3jZ/XHNV1nkhIjIH1/okukOkpaXByckJnp6eNn3cjIwMaJoGHx8fmz6uuSrrvBARmYMTNSKye/n5+XB2dq7swyAisjl+9UlUCVasWIFmzZrBzc0NNWrUQHR0NHJycgAARqMRsbGxiIiIgJubG1q0aIEVK1YUb9u5c2e8/PLLGDFiBHx9fREYGIjPP/8cOTk5GDRoEDw9PREZGYmff/7Z5DFv9RVfWfe7du1adOzYET4+PqhRowYefvhhHDt2rPjvb/7qMy8vD//3f/+HgIAAuLq6omPHjtixY4dyLMOGDcOIESPg7++PmJgY8ZhLe+zU1FQEBQXhvffeKx6/efNmODs7Iy4uTjwvpb0uesaPH49mzZrB3d0dgYGBGDJkCAoKCkrdhojIXJyoEdnY+fPn0b9/fzz77LM4dOgQ4uPj8fjjj+P6ze3Y2Fh8+eWXmDNnDg4cOIBXXnkFTz31FDZu3Fi8j4ULF8Lf3x/bt2/Hyy+/jCFDhqBPnz7o0KEDdu/ejW7duuHpp5/G5cuXLTq2suw3JycHI0eOxM6dOxEXFwcHBwc89thjMBqN4mOMHj0aK1euxMKFC7F7925ERkYiJiYGaWlpyrE4Ozvjjz/+wJw5c8R9lfbYNWvWxPz58/HOO+9g586dyMrKwtNPP41hw4aha9euFr8uEk3ToGka5s6di4MHD2LBggVYuXIl/vvf/5pzuomIbk0jIpvatWuXBkA7efKk8ne5ubla9erVtc2bN5vEn3vuOa1///6apmlap06dtI4dOxb/XWFhoebu7q49/fTTxbHz589rALQtW7YUxzp16qQNHz5c97jKut+bpaamagC0hIQETdM0beDAgVqvXr00TdO07OxszcnJSVu0aFHx+Pz8fC0kJESbNm2aybHcfffduo9h7mNrmqa99NJL2l133aX961//0po1a6bl5uYqz3v48OGlvi6W6N+/f6nnmYjIEryjRmRjLVq0QNeuXdGsWTP06dMHn3/+OS5dugQAOHr0KC5fvowHH3wQHh4exT9ffvmlydeJzZs3L/5vR0dH1KhRA82aNSuOBQYGAgBSUlLEY1i0aJHJ/n///fcy7/fIkSPo378/6tatCy8vL4SHhwMAEhMTlcc9duwYCgoKcO+99xbHnJyc0K5dOxw6dMhkbOvWrcVjL8mcx/7ggw9QWFiI5cuXY9GiRXBxcRH3VdrroufUqVMYOnQomjZtCl9fX3h4eOCbb75BWFjYLY+diMgc1Sr7AIjuNI6Ojli/fj02b96M//3vf/j000/x5ptvYtu2bcjOzgYA/PjjjwgNDTXZruQEw8nJyeTvDAaDScxgMACA7tePjz76KNq3b1/85+uPVZb9PvLII6hTpw4+//xzhISEwGg0omnTpsjPz7/FmSidu7v7LceY89jHjh3DuXPnYDQacfLkSZOJZ0mlvS4RERHK+NTUVLRt2xZdunTBRx99hNDQUBQVFaFNmzZo0aJF2Z84EVEJnKgRVQKDwYB7770X9957L8aNG4c6depg1apVGDx4MFxcXJCYmIhOnTpV2ON7enpapR3FxYsXcfjwYXz++ee47777AACbNm3SHV+vXr3ivLM6deoAAAoKCrBjxw6Le5mZ89j5+fl46qmn0LdvXzRo0ADPP/88EhISEBAQIO5T73UZOXKkMvb7779HUVERlixZUjyBnTlzJgoKCtCyZUuLngsRkR5O1IhsbNu2bYiLi0O3bt0QEBCAbdu2ITU1FY0aNYKnpydee+01vPLKKzAajejYsSMyMjLwxx9/wMvLCwMHDqzswzfh6+uLGjVq4LPPPkNwcDASExPx+uuv6453d3fHkCFDMGrUKPj5+aF27dqYNm0aLl++jOeee87qj/3mm28iIyMDn3zyCTw8PPDTTz/h2WefxQ8//KDsr7TXRVKjRg1kZmbiu+++Q+PGjfH9998jNjYWoaGhqFmzpkXPhYhIDydqRDbm5eWF3377DTNmzEBmZibq1KmDD/+/nTtEUSCKAzD+ockiGjyDYQRB5gBWw1RBcJJFiwewGrQIYvEATvAKJm1eQIyCZ7CKmHeX3WVhZZ7w/fqb+Q9TPt7wZrGg0+kAMJ1OqdVqzGYzLpcLlUqFVqvFZDLJefKvCoUC2+2W8XhMo9GgXq+zWq1ot9vfrpnP5zweD9I05Xa7Eccxu92OarX6r/c+HA4sl0v2+z3lchmAzWZDs9lkvV4zGo0+XO+39/JZkiQMBgPSNKVUKtHv9+l2u1yv1z89hyT9xB/eSnqpXq9HsVgky7K8R5Gkt+OpT0kvcb/fOZ/PHI9HoijKexxJekuGmqSXOJ1OxHFMFEUMh8O8x5Gkt+SnT0mSpEC5oyZJkhQoQ02SJClQhpokSVKgDDVJkqRAGWqSJEmBMtQkSZICZahJkiQFylCTJEkKlKEmSZIUKENNkiQpUE/ZK0fAz7PSnQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 700x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results2d = np.array(results).reshape(Ngrid,Ngrid)\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(7,5))\n",
    "ax = plt.subplot(111)\n",
    "extent = [min(par_a),max(par_a),min(par_e),max(par_e)]\n",
    "ax.set_xlim(extent[0],extent[1])\n",
    "ax.set_xlabel(\"semi-major axis $a$\")\n",
    "ax.set_ylim(extent[2],extent[3])\n",
    "ax.set_ylabel(\"eccentricity $e$\")\n",
    "im = ax.imshow(results2d, interpolation=\"none\", vmin=1.9, vmax=4, cmap=\"RdYlGn_r\", origin=\"lower\", aspect='auto', extent=extent)\n",
    "cb = plt.colorbar(im, ax=ax)\n",
    "cb.set_label(\"MEGNO $\\\\langle Y \\\\rangle$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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